Layer-wise Relevance Propagation Means More Interpretable Deep Learning
Wojciech Samek is head of machine learning for Fraunhofer Heinrich Hertz Institute. At ODSC Europe 2018, he spoke about an active area of research in deep learning: interpretability. Samek launched his lecture with the following preface on the rising importance of interpretability of deep learning models: “In the last number of... Read more
How to Play Fantasy Sports Strategically (and Win)
Daily Fantasy Sports is a multibillion-dollar industry with millions of annual users. The Imperial College Business School’s Martin Haugh created a framework to best those users by modeling what they’ll do and constructing a team based on it. Haugh presented his research on how to play Fantasy sports strategically... Read more
Mail Processing with Deep Learning: A Case Study
Businesses increasingly delegate simple, boring, and repetitive tasks to artificial intelligence. In a case study, Alexandre Hubert — lead data scientist of software company Dataiku’s U.K. operations — worked on a team of three to automate mail processing with deep learning. At ODSC Europe 2018, Hubert detailed how his team... Read more
Thomas Wiecki of Quantopian on ‘Minding the Gap’ Between Statistics and Machine Learning at ODSC Europe 2018
Key Takeaways: It’s important for data scientists to understand the so-called “gap” between statistics and machine learning, and how there actually is a lot of commonality between the two; it’s just a matter of how you look at things. PyMC3 is a very useful probabilistic programming framework for Python.... Read more
Active Learning: Your Model’s New Personal Trainer
First, some facts. Fact: active learning is not just another name for reinforcement learning; active learning is not a model; and no, active learning is not deep learning. What active learning is and why it may be an important component of your next machine learning project was the subject... Read more
ODSC Europe 2018 – Open Source Data Science Project Award Winner: PyMC3
Thanks to the efforts of academia, AI labs, and others, significant progress continues to be made in deep learning, machine learning, and data science in general. However, it’s thanks to the open source projects that many of these advances are quickly accessible to data scientist and developers. As such, we... Read more