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DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIANSEE MORE ONDATACRITICS.COM
SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ONDATACRITICS.COM
THIS AI CAN UPSCALE ANY IMAGE USING NEURAL Let’s Enhance is a free, online image upscale and enhancement that uses neural networks to increase image resolution and quality. Picture quality is now being added to photos— yes, after a photo has been captured. AI algorithms trained through neural networks are learning how brick, skin or hair appears, and can artificially generate dataDATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIANSEE MORE ONDATACRITICS.COM
SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ONDATACRITICS.COM
THIS AI CAN UPSCALE ANY IMAGE USING NEURAL Let’s Enhance is a free, online image upscale and enhancement that uses neural networks to increase image resolution and quality. Picture quality is now being added to photos— yes, after a photo has been captured. AI algorithms trained through neural networks are learning how brick, skin or hair appears, and can artificially generate data BASICS OF BLOCKCHAIN: LEARN-BY-DOING Basics of Blockchain: Learn-by-Doing. At its peak in December 2017, one Bitcoin was pushing $20K CDN. Yes, if you had possession of such a single virtual coin, you could sell it over the internet for $20K. In December 2018 its value dropped to around $5K. At the time of this article, its price is more than $10K – where will it end the yearR – DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. ORGANIZING YOUR FIRST TEXT ANALYTICS PROJECT Organizing Your First Text Analytics Project. Using Natural Language tools to uncover conversational data. Text analytics or text mining is the analysis of “unstructured” data contained in natural language text using various methods, tools and techniques. The popularity of text mining today is driven by statistics and the availability of UNDERSTANDING PREDICTIONS FROM BLACK BOX MODELS USING Understanding Predictions from Black Box Models using Shapley Values. When building a predictive model, a data scientist wants to identify the features with the strongest predictive powe r from a dataset. We examine model outputs and apply techniques to remove variables that are insignificant to produce a succinct model. ANALYTICS IN HR: GOOGLE’S PROJECT OXYGEN Project Oxygen. The big data analytics trend in HR is being adopted by large organizations. Google is one such multinational company that has been at the forefront of implementing big data analytics to bring improvement to its top-level management. Here is a breakdown of how Google did this, based on my research. WHAT’S YOUR TWITTER STORY? #TEXTMINING # This mini-project was inspired by Case study: comparing Twitter archives, a chapter in the wonderful book Text Mining with R written by Julia Silge and David Robinson. All code used can be found in this book, unless otherwise noted. I happen to be a (very) small contributor to the 500 million daily tweets that are shared onTwitter.
UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
LEARNING WITH YOUNGSTERS: NODE.JS & SPARK It's Christmas holidays as I write this, my first of four weeks off after completing the first half of my Data Analytics Certificate. I feel like taking a semi-break before trying to use most of this time off to get exposure to concepts I will be expected to learn in thesecond half of my
COLLECTING CANADIAN UNDERWRITER HEADLINES AND NFL BOX Collecting Canadian Underwriter Headlines and NFL Box Scores with Python. Oftentimes, the challenge in data science isn’t the science but obtaining data to conduct the study on—reliable, quality data that’s relevant to the questions being asked. Although much of the open-source data I’ve browsed these past months seems reliable, Ihad
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ONDATACRITICS.COM
THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIANSEE MORE ONDATACRITICS.COM
THIS AI CAN UPSCALE ANY IMAGE USING NEURAL Let’s Enhance is a free, online image upscale and enhancement that uses neural networks to increase image resolution and quality. Picture quality is now being added to photos— yes, after a photo has been captured. AI algorithms trained through neural networks are learning how brick, skin or hair appears, and can artificially generate data UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ONDATACRITICS.COM
TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIANSEE MORE ONDATACRITICS.COM
HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. THIS AI CAN UPSCALE ANY IMAGE USING NEURAL Let’s Enhance is a free, online image upscale and enhancement that uses neural networks to increase image resolution and quality. Picture quality is now being added to photos— yes, after a photo has been captured. AI algorithms trained through neural networks are learning how brick, skin or hair appears, and can artificially generate data UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. BASICS OF BLOCKCHAIN: LEARN-BY-DOING Basics of Blockchain: Learn-by-Doing. At its peak in December 2017, one Bitcoin was pushing $20K CDN. Yes, if you had possession of such a single virtual coin, you could sell it over the internet for $20K. In December 2018 its value dropped to around $5K. At the time of this article, its price is more than $10K – where will it end the yearR – DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. ORGANIZING YOUR FIRST TEXT ANALYTICS PROJECT Organizing Your First Text Analytics Project. Using Natural Language tools to uncover conversational data. Text analytics or text mining is the analysis of “unstructured” data contained in natural language text using various methods, tools and techniques. The popularity of text mining today is driven by statistics and the availability of UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
UNDERSTANDING PREDICTIONS FROM BLACK BOX MODELS USING Understanding Predictions from Black Box Models using Shapley Values. When building a predictive model, a data scientist wants to identify the features with the strongest predictive powe r from a dataset. We examine model outputs and apply techniques to remove variables that are insignificant to produce a succinct model. HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. LEARNING TO SELL DATA PROJECTS, STARTING IN YOUR LOCAL Learning to Sell Data Projects, Starting in Your Local Community. How I’ve sold my data science skills starting on community boards. I recently posted an ad on Kijiji to sell light-medium data projects, like scraping public datasets from websites, R development, or helping with Excel & PowerPivot. These were the data science and data SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: WHAT’S YOUR TWITTER STORY? #TEXTMINING # This mini-project was inspired by Case study: comparing Twitter archives, a chapter in the wonderful book Text Mining with R written by Julia Silge and David Robinson. All code used can be found in this book, unless otherwise noted. I happen to be a (very) small contributor to the 500 million daily tweets that are shared onTwitter.
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIANSEE MORE ONDATACRITICS.COM
USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ONDATACRITICS.COM
HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: THIS AI CAN UPSCALE ANY IMAGE USING NEURAL Let’s Enhance is a free, online image upscale and enhancement that uses neural networks to increase image resolution and quality. Picture quality is now being added to photos— yes, after a photo has been captured. AI algorithms trained through neural networks are learning how brick, skin or hair appears, and can artificially generate data UNDERSTANDING PREDICTIONS FROM BLACK BOX MODELS USINGSEE MORE ONDATACRITICS.COM
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIANSEE MORE ONDATACRITICS.COM
USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ONDATACRITICS.COM
HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: THIS AI CAN UPSCALE ANY IMAGE USING NEURAL Let’s Enhance is a free, online image upscale and enhancement that uses neural networks to increase image resolution and quality. Picture quality is now being added to photos— yes, after a photo has been captured. AI algorithms trained through neural networks are learning how brick, skin or hair appears, and can artificially generate data UNDERSTANDING PREDICTIONS FROM BLACK BOX MODELS USINGSEE MORE ONDATACRITICS.COM
TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.R – DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. BASICS OF BLOCKCHAIN: LEARN-BY-DOING Basics of Blockchain: Learn-by-Doing. At its peak in December 2017, one Bitcoin was pushing $20K CDN. Yes, if you had possession of such a single virtual coin, you could sell it over the internet for $20K. In December 2018 its value dropped to around $5K. At the time of this article, its price is more than $10K – where will it end the year UNDERSTANDING PREDICTIONS FROM BLACK BOX MODELS USING Understanding Predictions from Black Box Models using Shapley Values. When building a predictive model, a data scientist wants to identify the features with the strongest predictive powe r from a dataset. We examine model outputs and apply techniques to remove variables that are insignificant to produce a succinct model. HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. ANALYTICS IN HR: GOOGLE’S PROJECT OXYGEN Project Oxygen. The big data analytics trend in HR is being adopted by large organizations. Google is one such multinational company that has been at the forefront of implementing big data analytics to bring improvement to its top-level management. Here is a breakdown of how Google did this, based on my research. BUILD-A-GGPLOT: THE FALL OF THE SIMPSONS Today we incorporate a bit of television history with our data The Simpsons TV show needs little introduction—it is well-received as one of the pioneering “made for adults” cartoons.It rose to popularity with characters who were carefully developed with clearmorals so
UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
THE IMPORTANCE OF DETERMINATION FOR NEW DATA SCIENTISTS Half a year ago, I was clueless about my future. I wanted to learn a skill that could be used for a long-term career. I saw how fast data analytics was growing in the technology and information age, and realized I could learn an in-demand skill which would equip me with the power to analyze big datasets and uncover a business’ weaknesses or missed opportunities. WHAT’S YOUR TWITTER STORY? #TEXTMINING # This mini-project was inspired by Case study: comparing Twitter archives, a chapter in the wonderful book Text Mining with R written by Julia Silge and David Robinson. All code used can be found in this book, unless otherwise noted. I happen to be a (very) small contributor to the 500 million daily tweets that are shared onTwitter.
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our dataDATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ONDATACRITICS.COM
THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIANSEE MORE ONDATACRITICS.COM
HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. BUILD-A-GGPLOT: THE FALL OF THE SIMPSONS Today we incorporate a bit of television history with our data The Simpsons TV show needs little introduction—it is well-received as one of the pioneering “made for adults” cartoons.It rose to popularity with characters who were carefully developed with clearmorals so
THIS AI CAN UPSCALE ANY IMAGE USING NEURAL Let’s Enhance is a free, online image upscale and enhancement that uses neural networks to increase image resolution and quality. Picture quality is now being added to photos— yes, after a photo has been captured. AI algorithms trained through neural networks are learning how brick, skin or hair appears, and can artificially generate data TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.R – DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: UNDERSTANDING PREDICTIONS FROM BLACK BOX MODELS USING Understanding Predictions from Black Box Models using Shapley Values. When building a predictive model, a data scientist wants to identify the features with the strongest predictive powe r from a dataset. We examine model outputs and apply techniques to remove variables that are insignificant to produce a succinct model. ORGANIZING YOUR FIRST TEXT ANALYTICS PROJECT Organizing Your First Text Analytics Project. Using Natural Language tools to uncover conversational data. Text analytics or text mining is the analysis of “unstructured” data contained in natural language text using various methods, tools and techniques. The popularity of text mining today is driven by statistics and the availability of HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. ANALYTICS IN HR: GOOGLE’S PROJECT OXYGEN Project Oxygen. The big data analytics trend in HR is being adopted by large organizations. Google is one such multinational company that has been at the forefront of implementing big data analytics to bring improvement to its top-level management. Here is a breakdown of how Google did this, based on my research. UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
WHAT’S YOUR TWITTER STORY? #TEXTMINING # This mini-project was inspired by Case study: comparing Twitter archives, a chapter in the wonderful book Text Mining with R written by Julia Silge and David Robinson. All code used can be found in this book, unless otherwise noted. I happen to be a (very) small contributor to the 500 million daily tweets that are shared onTwitter.
COLLECTING CANADIAN UNDERWRITER HEADLINES AND NFL BOX Collecting Canadian Underwriter Headlines and NFL Box Scores with Python. Oftentimes, the challenge in data science isn’t the science but obtaining data to conduct the study on—reliable, quality data that’s relevant to the questions being asked. Although much of the open-source data I’ve browsed these past months seems reliable, Ihad
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIAN After some data collection and wrangling projects, I decided it was time to explore trends and insights in Canadian Underwriter data using text mining and sentiment analysis.. Some of my colleagues have already done compelling work in this area, which I reference at the end of this article. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ON DATACRITICS.COMFANTASY FOOTBALL DATAFREE FANTASY FOOTBALL DATA SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIAN After some data collection and wrangling projects, I decided it was time to explore trends and insights in Canadian Underwriter data using text mining and sentiment analysis.. Some of my colleagues have already done compelling work in this area, which I reference at the end of this article. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ON DATACRITICS.COMFANTASY FOOTBALL DATAFREE FANTASY FOOTBALL DATA SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.PERSPECTIVE
Scraping & Plotting: Who Is the “Worst” Bachelor? Data Scientists gather data to prove once and for all who the worst Bachelor was. by Sakshi Gupta. August 25, 2018 11. Exploratory Data Analysis Lexicons NLP Perspective R Sentiment Analysis Text Analytics.R – DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. BASICS OF BLOCKCHAIN: LEARN-BY-DOING Basics of Blockchain: Learn-by-Doing. At its peak in December 2017, one Bitcoin was pushing $20K CDN. Yes, if you had possession of such a single virtual coin, you could sell it over the internet for $20K. In December 2018 its value dropped to around $5K. At the time of this article, its price is more than $10K – where will it end the year HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. LEARNING TO SELL DATA PROJECTS, STARTING IN YOUR LOCAL Learning to Sell Data Projects, Starting in Your Local Community. How I’ve sold my data science skills starting on community boards. I recently posted an ad on Kijiji to sell light-medium data projects, like scraping public datasets from websites, R development, or helping with Excel & PowerPivot. These were the data science and data ANALYTICS IN HR: GOOGLE’S PROJECT OXYGEN Project Oxygen. The big data analytics trend in HR is being adopted by large organizations. Google is one such multinational company that has been at the forefront of implementing big data analytics to bring improvement to its top-level management. Here is a breakdown of how Google did this, based on my research. WHAT’S YOUR TWITTER STORY? #TEXTMINING # This mini-project was inspired by Case study: comparing Twitter archives, a chapter in the wonderful book Text Mining with R written by Julia Silge and David Robinson. All code used can be found in this book, unless otherwise noted. I happen to be a (very) small contributor to the 500 million daily tweets that are shared onTwitter.
UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIAN After some data collection and wrangling projects, I decided it was time to explore trends and insights in Canadian Underwriter data using text mining and sentiment analysis.. Some of my colleagues have already done compelling work in this area, which I reference at the end of this article. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ON DATACRITICS.COMFANTASY FOOTBALL DATAFREE FANTASY FOOTBALL DATA SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIAN After some data collection and wrangling projects, I decided it was time to explore trends and insights in Canadian Underwriter data using text mining and sentiment analysis.. Some of my colleagues have already done compelling work in this area, which I reference at the end of this article. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ON DATACRITICS.COMFANTASY FOOTBALL DATAFREE FANTASY FOOTBALL DATA SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.PERSPECTIVE
Scraping & Plotting: Who Is the “Worst” Bachelor? Data Scientists gather data to prove once and for all who the worst Bachelor was. by Sakshi Gupta. August 25, 2018 11. Exploratory Data Analysis Lexicons NLP Perspective R Sentiment Analysis Text Analytics.R – DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. BASICS OF BLOCKCHAIN: LEARN-BY-DOING Basics of Blockchain: Learn-by-Doing. At its peak in December 2017, one Bitcoin was pushing $20K CDN. Yes, if you had possession of such a single virtual coin, you could sell it over the internet for $20K. In December 2018 its value dropped to around $5K. At the time of this article, its price is more than $10K – where will it end the year HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. LEARNING TO SELL DATA PROJECTS, STARTING IN YOUR LOCAL Learning to Sell Data Projects, Starting in Your Local Community. How I’ve sold my data science skills starting on community boards. I recently posted an ad on Kijiji to sell light-medium data projects, like scraping public datasets from websites, R development, or helping with Excel & PowerPivot. These were the data science and data ANALYTICS IN HR: GOOGLE’S PROJECT OXYGEN Project Oxygen. The big data analytics trend in HR is being adopted by large organizations. Google is one such multinational company that has been at the forefront of implementing big data analytics to bring improvement to its top-level management. Here is a breakdown of how Google did this, based on my research. WHAT’S YOUR TWITTER STORY? #TEXTMINING # This mini-project was inspired by Case study: comparing Twitter archives, a chapter in the wonderful book Text Mining with R written by Julia Silge and David Robinson. All code used can be found in this book, unless otherwise noted. I happen to be a (very) small contributor to the 500 million daily tweets that are shared onTwitter.
UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIAN After some data collection and wrangling projects, I decided it was time to explore trends and insights in Canadian Underwriter data using text mining and sentiment analysis.. Some of my colleagues have already done compelling work in this area, which I reference at the end of this article. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ON DATACRITICS.COMFANTASY FOOTBALL DATAFREE FANTASY FOOTBALL DATA SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
DATACRITICS
DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. TEAM – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. QUICKLY VISUALIZE ALL VARIABLES IN A NEW DATASET Visualize All Variables. For convenience—and convenience is always welcomed in data science—let’s continue to look at the rest of the Boston dataset using ggplot2‘s Small Multiple Chart.. First, we start by “melting” our data from a wide format into a long format.We will need to call the reshape2 package to perform this.Take a look at the code below for the transformation our data GET BETTER AT GRAPHING CATEGORICAL DATA WITH GGPLOT2SEE MORE ONDATACRITICS.COM
HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. TEXT MINING AND SENTIMENT ANALYSIS WITH CANADIAN After some data collection and wrangling projects, I decided it was time to explore trends and insights in Canadian Underwriter data using text mining and sentiment analysis.. Some of my colleagues have already done compelling work in this area, which I reference at the end of this article. USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMESSEE MORE ON DATACRITICS.COMFANTASY FOOTBALL DATAFREE FANTASY FOOTBALL DATA SCRAPE-IT-YOURSELF: SPOTIFY CHARTS We want to replicate a URL over the range of pages we want our scraper to pull from. I determined my range will be Daily, Top 200, and Canadian hits from the month of February.. We need to find the variable that defines the way pages are listed on the site and loop it into the constant. A little investigation is all that’s required: HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITY Open Global Options in RStudio. 2. Go to the Code Tab and Edit Snippets (make sure it’s enabled). 3. Choose your language and begin writing. Note: making sure snippets are correctly saved is important. They can be finicky. Some quick things to troubleshoot: Make sure the word “snippet” is blue. THREE TEXT SENTIMENT LEXICONS IN R’S TIDYTEXT For this blog post, I would like to share my exploration of three different lexicons in R's tidytext from my last post on sentiment analysis. This is also an opportunity to re-ground oneself in tidy data1 principles, and showcase the tidytext package. The simplicity and efficiency of tidytext will allow you to get creative with youranalysis using
LEARNING – DATACRITICS and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along.PERSPECTIVE
Scraping & Plotting: Who Is the “Worst” Bachelor? Data Scientists gather data to prove once and for all who the worst Bachelor was. by Sakshi Gupta. August 25, 2018 11. Exploratory Data Analysis Lexicons NLP Perspective R Sentiment Analysis Text Analytics.R – DATACRITICS
and welcome to the wonderful world of predictive analytics, machine learning and AI! DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. BASICS OF BLOCKCHAIN: LEARN-BY-DOING Basics of Blockchain: Learn-by-Doing. At its peak in December 2017, one Bitcoin was pushing $20K CDN. Yes, if you had possession of such a single virtual coin, you could sell it over the internet for $20K. In December 2018 its value dropped to around $5K. At the time of this article, its price is more than $10K – where will it end the year HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap. LEARNING TO SELL DATA PROJECTS, STARTING IN YOUR LOCAL Learning to Sell Data Projects, Starting in Your Local Community. How I’ve sold my data science skills starting on community boards. I recently posted an ad on Kijiji to sell light-medium data projects, like scraping public datasets from websites, R development, or helping with Excel & PowerPivot. These were the data science and data ANALYTICS IN HR: GOOGLE’S PROJECT OXYGEN Project Oxygen. The big data analytics trend in HR is being adopted by large organizations. Google is one such multinational company that has been at the forefront of implementing big data analytics to bring improvement to its top-level management. Here is a breakdown of how Google did this, based on my research. WHAT’S YOUR TWITTER STORY? #TEXTMINING # This mini-project was inspired by Case study: comparing Twitter archives, a chapter in the wonderful book Text Mining with R written by Julia Silge and David Robinson. All code used can be found in this book, unless otherwise noted. I happen to be a (very) small contributor to the 500 million daily tweets that are shared onTwitter.
UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS Uncovering Hidden Trends in AirBnB Reviews. As promised in my previous blog, this is your next guide to understanding the basics of sentiment analysis on text documents and how to extract their hidden emotions. Technical foundation for this blog comes from DataCamp’s SentimentAnalysis in R.
DATACRITICS
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HOW RSTUDIO SNIPPETS IMPROVE MY PRODUCTIVITYby Jake Daniels
January 28, 2019
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BASICS OF BLOCKCHAIN: LEARN-BY-DOING Building blockchain with Python object oriented programming by Gordon Yun November22, 2018
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LEARNING TO SELL DATA PROJECTS, STARTING IN YOUR LOCAL COMMUNITY How I’ve sold my data science skills starting on community boards. by Gordon Yun November 6,2018
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USING DATA SCIENCE TO HELP WIN FANTASY FOOTBALL GAMES A couple years into my first fantasy football league, I felt the need to track game statistics to find hiddenContinue Reading by Tian October 2, 2018Number of comments0
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UNDERSTANDING PREDICTIONS FROM BLACK BOX MODELS USING SHAPLEY VALUES When building a predictive model, a data scientist wants to identify the features with the strongest predictive power from a dataset.Continue ReadingPOSTS NAVIGATION
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HELLO FUTURE DATA SCIENTISTS _… AND WELCOME TO THE WONDERFUL WORLD OF PREDICTIVE ANALYTICS, MACHINE LEARNING AND AI!_ DataCritics is a community of data scientists sharing our individual journeys into the emerging field of big data while also finding some meaningful resources to help you along. As you progress on this challenging yet rewarding quest to become a better data scientist, we want to help make things less complicated. We hope you stay and get to know us! ~ The DataCritics TeamSearch for:
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WELCOMING STUDENTS WITH SOCIAL WORDCLOUDS Learn to get tweets to make a colourful wordcloudby Jake Daniels
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PREDICTING POPULARITY OF THE NEW YORK TIMES COMMENTS (PART 1) elxn2018 IntermediateLearning
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#ELXN2018 IN R: ONTARIO TWEETERS’ TOP PRIORITY IS HEALTHCAREFree Intermediate
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UNCOVERING HIDDEN TRENDS IN AIRBNB REVIEWS CAREER PERSPECTIVESEE ALL POSTSBeginner Hadoop
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ROLLING UP THE SLEEVES ON MY FIRST DATA PROJECT Exploring Toronto Data with R and Hive Beginner Perspective HOW TO MASTER DATA BENDING How many times have you started out with a clear idea on goals and techniques and finally found yourself lost in the maze of big data? If your answer is “quite often”, this article might help you find a way out. Or even better, not fall prey to this trap.Beginner Hadoop
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TGIF: THE GRIND INCLUDES FRIDAYS Now that I’m halfway through the winter semester, I thought a reflection on my Christmas study break was long overdue.ContinueReading
Beginner Machine
Learning
Perspective
STATISTICS AND MACHINE LEARNING: WE ARE A COUPLE BUT WE ARE DIFFERENT As a beginner in data science, there are two concepts you cannot ignore: statistics and machine learning. Sometimes you mayContinueReading
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