This week, Boris, Xiao, and Carly share recent reads about MOOCs, collusion in AI pricing, and generating fake news with artificial intelligence.
… Continue readingHow to Increase Retention and Revenue in 1,000 Nontrivial Steps
Yanir reflects on how data scientists at Automattic work to improve customer retention.
… Continue readingBuilding Thousands of Reproducible ML Models with pipe, the Automattic Machine Learning Pipeline
Demet takes you deep into pipe, a tool that allows anyone at Automattic to build solid machine learning models.
… Continue readingMissed Opportunities for Using Text in Data Visualization
Richard Brath talks to Automattic data visualization enthusiasts about the power of text in conveying the results of data science.
… Continue readingLinks Worth Sharing: What Makes People Successful
Boris shares a paper and a podcast all about the science of success.
… Continue readingIntroducing pipe, The Automattic Machine Learning Pipeline
Demet gives us an overview of pipe, Automattic's machine learning pipeline.
… Continue readingLinks Worth Sharing: The Training and Security of Neural Networks
This week, Charles shares a couple of talks he enjoyed on neural networks at Georgia Tech's Theoretical Foundation of Deep Learning conference.
… Continue reading