Data Science Platforms: Guides, Tutorials,, and How to Pick the Best One

EXPLORATORY ANALYSIS – WHEN TO CHOOSE R, PYTHON, TABLEAU OR A COMBINATION

Platforms Python R Tools & Languages Data Science|Data Visualization|Programming Language|Python|Rposted by Scott Stoltzman March 14, 2018

Not all data analysis tools are created equal. Recently, I started looking into data sets to compete in Go Code Colorado (check it out if you live in CO). The problem with such diversity in data sets is finding a way to quickly visualize the data and do... Read more

Interview with Ross Taylor, Founder of Throne AI

Platforms Tools & Languages Data analysis|Modeling|Open Data|Open Data Science|Sports Analyticsposted by George McIntire, ODSC March 8, 2018

In a previous post, I wrote about Throne AI, a sports prediction platform or “Kaggle for sports.” If you’re a sports fan and interested in using your machine learning abilities to predict the outcome of sports matches, then I highly recommend you sign up for Throne... Read more

Test-Driving Apache Superset

DataOps DS @ Scale Platforms Tools & Languages Apache|Data analysis|Open Data Scienceposted by SmartCat Data Science Team March 6, 2018

The Curious Case of Algo-Trading Dashboard For one of our recent internal projects, we needed a quick and easy way to showcase some first insights, do some plotting and interactive storytelling with the data. We also wanted to build a live, working dashboard in front of... Read more

Git First-Parent– Have your messy history and eat it too

Platforms Tools & Languagesposted by David Chudzicki March 4, 2018

Intro The first thing I encountered learning about git: there’s a lot of conflict about whether it’s important to keep a “clean” git history by squashing, rebasing instead of merging, etc. In favor of ‘cleanliness’ 1: git log shows the higher-level history most people will care more about... Read more

The New Facebook Algorithm: Secrets Behind How It Works and What You Can Do To Succeed

Platforms Tools & Languages Algorithms|Data analysis|Facebook|Social Network Analysisposted by Buffer Team February 27, 2018

The Facebook algorithm is constantly evolving in order to provide a better experience for users. But few changes to the algorithm have sparked as much interest and conversation as the recent ‘meaningful interactions’ update, in which Facebook said it would be prioritizing posts that create meaningful conversations,... Read more

WHAT PROGRAMMING LANGUAGES ARE USED MOST ON WEEKENDS?

Platforms Python R Tools & Languages Data analysis|Kaggle Analysis|Programming Language|SQLposted by Julia Silge February 22, 2018

Note: Cross-posted with the Stack Overflow blog. Check out the code for this analysis on Kaggle. For me, the weekends are mostly about spending time with my family, reading for leisure, and working on the open-source projects I am involved in. These weekend projects overlap with the work... Read more

Should You Put Several Event Types in the Same Kafka Topic?

Platforms Tools & Languages Algorithms|Apache|Apache Kafka|streaming platformposted by Martin Kleppmann February 20, 2018

If you adopt a streaming platform such as Apache Kafka, one of the most important questions to answer is: what topics are you going to use? In particular, if you have a bunch of different events that you want to publish to Kafka as messages, do you put them... Read more

Failure to replicate Schwartz-Ziv and Tishby

Deep Learning Modeling Platforms Tools & Languagesposted by Aaron Schumacher February 13, 2018

Opening the Black Box of Deep Neural Networks via Information didn’t appear at any conferences, to my knowledge, but it still built up some buzz. It has been difficult to replicate, for both bloggers and academics. I attempted to replicate some aspects, and emailed the authors with the message below in... Read more

How To Create Data Products That Are Magical Using Sequence-to-Sequence Models

Data Wrangling Modeling Platforms Tools & Languages Workflow Deep Learning|Machine Learning|NLPposted by Hamel Husain January 30, 2018

A tutorial on how to summarize text and generate features from Github Issues using deep learning with Keras and TensorFlow. Teaser: Training a model to summarize Github Issues Predictions are in rectangular boxes. The above results are randomly selected elements of a holdout set. Keep reading below, there will be a link... Read more