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Most Influential Data Science Research Papers for 2018

Featured Post Modeling Research Researchposted by Daniel Gutierrez, ODSC December 19, 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 October Research

Research Researchposted by Paxtyn Merten November 13, 2018

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 about revelations researchers made and how they applied machine learning, deep... Read more

AI-Identified Health Policies, Hate Speech Detection Among September Industry Research

Researchposted by Paxtyn Merten October 12, 2018

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

Modeling Researchposted by Priya Dwivedi August 8, 2018

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

Modeling Researchposted by Julien Simon August 3, 2018

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

Modeling Researchposted by Marcelo Rinesi August 1, 2018

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

Modeling Researchposted by Kristen Kehrer July 27, 2018

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

How Well Did Data Scientists Predict the 2018 World Cup? (Hint: Not Very)

Data Wrangling Modeling Predictive Analytics Research Statistics popular culture world cupposted by Alex Amari July 26, 2018

This year’s World Cup in Russia was the most watched sporting event in history. GlobalWebIndex reports that up to 3.4 billion people – around half of the world’s population – watched some part of the tournament. As with past World Cups, a global prediction market emerged allowing spectators to... Read more

A Real World Reinforcement Learning Research Program

Modeling Researchposted by John Langford July 19, 2018

We are hiring for reinforcement learning related research at all levels and all MSR labs. If you are interested, apply, talk to me at COLT or ICML, or email me. More generally though, I wanted to lay out a philosophy of research which differs from (and plausibly improves on) the current prevailing mode. Deepmind and OpenAI have popularized an... Read more

My Latent Dissatisfaction with Modern ML

Modeling Researchposted by Eric Ma July 3, 2018

It took reading Judea Pearl’s “The Book of Why”, and Jonas Peters’ mini-course on causality, for me to finally figure out why I had this lingering dissatisfaction with modern machine learning. It’s because modern machine learning (deep learning included) is most commonly used as a tool in the service... Read more