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Best Machine Learning Research of 2019
The field of machine learning has continued to accelerate through 2019, moving at light speed with compelling new results coming out of academia and the research arms of large tech firms like Google, Microsoft, Yahoo, Facebook and many more. It’s a daunting task for the down-in-the-trenches data scientist to... Read more
Data Science News Week in Review: November 25th
Every week we’re bringing data science news to you… some highlights include reviewing Facebook’s DeepFovea AI, IBM’s Consortium for Sequencing the Food Supply Chain, and more. Read on: Facebook’s DeepFovea AI promises power-efficient VR foveated rendering In a paper released on November 18th, Facebook introduced a human-like “peripheral vision”... Read more
7 AI Research Labs in Europe Leading the Data Science Community
In the past, we’ve highlighted some West Coast AI research labs that we think are doing some really incredible work. Now, in an attempt to look past the dominating presence of Silicon Valley, we’re turning our focus overseas and taking a closer look at some of the cutting-edge Europe... Read more
Most Influential Data Science Research Papers for 2018
As an academic researcher in a previous life, I like to maintain ties to the research community while working in the data science field. I feel that a firm understanding of the origins for the technologies I use in my consulting work: AI, machine learning, and deep learning, helps... Read more
Self-Driving Cars, Generated News Among Top Data Science Research
Self-driving cars. Less biased crowdsourced data. Automatically generated historical accounts. These are some of the topics data science researchers across the world tackled and published to the arXiv research aggregator out of Cornell University Library in October. Learn... Read more
AI-Identified Health Policies, Hate Speech Detection Among September Industry Research
September has been an impressive month for data science research. Here, we highlight a few innovative and explosive studies released on the arXiv research aggregator out of Cornell University Library. This research dives into some of the most important facets of data science today, including deep learning, machine learning,... Read more
Analyze a Soccer Game Using Tensorflow Object Detection and OpenCV
Introduction The world cup season is here and off to an interesting start. Whoever thought the reigning champions Germany would be eliminated in the group stage 🙁 For the data scientist within you, lets use this opportunity to do some analysis on soccer clips. With the use of deep learning... Read more
Mastering the Mystical Art of Model Deployment
With all the talk about algorithm selection, hyper parameter optimization and so on, you could think that training models is the hardest part of the Machine Learning process. However, in my experience, the really tricky step is to deploy these models safely in a web production environment. In this... Read more
Mapping the Shifting Constellations of Online Debate
Online conversations, specially around contentious topics, are complex and dynamic. Mapping them is not just a matter of gathering enough data and applying sophisticated algorithms. It’s critical to adjust the map to the questions you want to answer; like models in general, no map is true, but some are... Read more
Learning with A/B Testing
I’ve spent the last 6 years of my life heavily involved in A/B testing, and other testing methodologies.  Whether it was the performance of an email campaign to drive health outcomes,  product changes, Website changes, the example list goes on. A few of these tests have been full factorial... Read more