- The Mueller Report Word Cloud: A brief tutorial in R - Apr 22, 2019.
Word clouds are simple visual summaries of the mostly frequently used words in a text, presenting essentially the same information as a histogram but are somewhat less precise and vastly more eye-catching. Get a quick sense of the themes in the recently released Mueller Report and its 448 pages of legal content.
- Generating Text with RNNs in 4 Lines of Code - Jun 14, 2018.
Want to generate text with little trouble, and without building and tuning a neural network yourself? Let's check out a project which allows you to "easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code."
- Find Out What Celebrities Tweet About the Most - Oct 5, 2017.
Word cloud is a popular data visualisation method. Here we show how to use R to create twitter word cloud of celebrities and politicians.
- Does the Muslim Ban Make Us Safer?: Data Science vs Fake News - Apr 5, 2017.
An obvious metric we can look at for how much harm terrorists from the banned countries do to America is looking at the number of people killed on American soil by terrorists from these countries.
- What Happened Last Night in Sweden: Data Science vs Fake News - Mar 22, 2017.
During a rally in February, President Trump had these disparaging words about Sweden’s humane immigration policy... but nothing of note actually happened the previous night in Sweden.
- Data Science vs Fake News Contest - Feb 27, 2017.
Submit a story that clearly exposes a false claim in the news, using data and visualization. This contest is sponsored by KDnuggets, Data For Democracy, and data.world. Submissions due March 10, 2017.
- KDnuggets™ News 17:n07, Feb 22: 17 Must-Know Data Science Interview Q&A; Removing Outliers in Python - Feb 22, 2017.
Also Removing Outliers Using Standard Deviation in Python; Natural Language Processing Key Terms, Explained; Data Scientists Strongly Oppose Trump Immigration Ban.
- Data Scientists Strongly Oppose Trump Immigration Ban - Feb 21, 2017.
Latest poll of nearly 1000 analytics professionals and data scientists who read KDnuggets shows that 75% worldwide and 77% in the US oppose Trump Immigration Ban. The poll results reveal sharp polarization, with strong views prevailing on both sides.
- 17 More Must-Know Data Science Interview Questions and Answers - Feb 15, 2017.
17 new must-know Data Science Interview questions and answers include lessons from failure to predict 2016 US Presidential election and Super Bowl LI comeback, understanding bias and variance, why fewer predictors might be better, and how to make a model more robust to outliers.
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- What Americans Really Think About Trump’s Immigration Ban and Why - Feb 9, 2017.
What do Americans really think of the President's immigration ban? Text analysis of what people say in their own words reveals more than multiple-choice surveys.
- New Poll: Do you support Trump Immigration Ban? - Feb 9, 2017.
Express your opinion about Trump Immigration ban and find out what does Google Autocomplete offers when you search for "Trump Immigration".
- KDnuggets Top Blogs and Bloggers in November 2016 - Dec 8, 2016.
We recognize the best KDnuggets Bloggers who had the most popular blogs by views or social media shares in November 2016.
- Trump, The Statistics of Polling, and Forecasting Home Prices - Nov 12, 2016.
Why polling has failed in US Presidential election? The home price index offers an apt comparison inasmuch as sample selection is problematic, equally snagging both election predictions and home price futures.
- KDnuggets™ News 16:n40, Nov 9: Trump, Failure of Prediction, and Lessons for Data Scientists; 8 Frustrating Things For R Users When Learning Python - Nov 9, 2016.
We examine the lessons for Data Scientists from the shocking and surprising win of Donald Trump; 8 frustrating things for R user when learning Python; Using Predictive Algorithms to Track Real Time Health Trends.
- Trump, Failure of Prediction, and Lessons for Data Scientists - Nov 9, 2016.
The shocking and unexpected win of Donald Trump of presidency of the United States has once again showed the limits of Data Science and prediction when dealing with human behavior.
- An NLP Approach to Analyzing Twitter, Trump, and Profanity - Nov 3, 2016.
Who swears more? Do Twitter users who mention Donald Trump swear more than those who mention Hillary Clinton? Let’s find out by taking a natural language processing approach (or, NLP for short) to analyzing tweets.
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- The Trump Phenomenon: A Twitter Based Recount - Sep 26, 2016.
This analysis uses Twitter data to perform a sentiment analysis to help determine how people truly feel about Trump. We found that while his fans have supported him throughout his entire campaign, more and more Twitter users have started to grow tired of Trump’s attitude.
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- Cartoon: Make Data Great Again - Aug 13, 2016.
This KDnuggets cartoon considers a speech that a certain presidential candidate can give on a topic of Big Data.
- Political Data Science: Analyzing Trump, Clinton, and Sanders Tweets and Sentiment - Jun 18, 2016.
This post shares some results of political text analytics performed on Twitter data. How negative are the US Presidential candidate tweets? How does the media mention the candidates in tweets? Read on to find out!
- Top KDnuggets tweets, Feb 29 – Mar 06: Data Science Process; Wisdom of Crowds fails to solve this simple puzzle - Mar 7, 2016.
Wisdom of Crowds fails to solve this simple #math #puzzle ; #DataScience Process - the work flow of a data scientist; R is the fastest-growing language on #StackOverflow; @DeepDrumpf #DeepLearning #Twitterbot imitates #DTrump, more plausible than real one.
- Trump vs Clinton – What are the Odds? - Mar 7, 2016.
Even with 5% advantage for Clinton, statistical analysis and examining how undecided break towards these candidates, we estimate a 25%-30% chance that Trump would be elected president.
- Top KDnuggets tweets, Feb 22-28: Quantifying Similarity in Structured Data; #Oscar #DataScience: 4-5 nominations no guarantee of winning - Feb 29, 2016.
A Statistical View of #DeepLearning; Impressive tutorial - Tree Kernels: Quantifying Similarity in Structures; Conversation with Data Scientist Sebastian Raschka - new podcast; How to become a #Bayesian in eight easy steps.
- Visualizing Unstructured Analysis – Elections, Words, and Zika virus - Feb 15, 2016.
Unstructured data has proven to be a big analytics challenge. This week in the Data Driven Digest, we’re serving up some ingenious visualizations of unstructured data and making it talk.
- Money vs Votes in New Hampshire Primary – SuperPACs not very effective - Feb 12, 2016.
We examine the money and votes in New Hampshire 2016 Primary. Over $100 million was spent by all campaigns, with hugely varying results, and no apparent correlation between money and votes.
- Money does buy votes, unless you are Jeb Bush - Feb 3, 2016.
Can money buy votes? In Iowa republican caucuses Jeb Bush spent about $2,700/per vote, with little to show. However, without Jeb, there is a strong correlation between money and votes, with $210/vote on average. We also find that spending more time in Iowa does not help.