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Accelerating Deep Learning Recommender Systems by Over 15x Using RAPIDS, PyTorch, and fast.ai
This June, the RAPIDS Deep Learning team took part in the RecSys 2019 Challenge, where we placed 15th out of 1534 teams despite joining the competition in its final weeks. The competition centered around recommending hotel listings to users of the website Trivago, who was the host of the... Read more
Opening The Black Box—Interpretability In Deep Learning
Editor’s Note: See Joris and Matteo at their tutorial “Opening The Black Box — Interpretability in Deep Learning” at ODSC Europe 2019 this November 20th in London. Why interpretability?  In the last decade, the application of deep neural networks to long-standing problems has brought a breakthrough... Read more
Deep Learning with TensorFlow 2.0
Editor’s Note: See Jon’s talk “Deep Learning with TensorFlow 2.0” at ODSC West 2019.  This summer, I had a blast speaking at Immersive A.I.—the first annual Open Data Science Conference (ODSC) event in New York. The venue was flawless, the organizers were exceptionally well-prepared, and there... Read more
Best Deep Reinforcement Learning Research of 2019 So Far
In this article, I’ve conducted an informal survey of all the deep reinforcement learning research thus far in 2019 and I’ve picked out some of my favorite papers. This list should make for some enjoyable summer reading!   [Related Article: 10 Compelling Machine Learning Dissertations from Ph.D.... Read more
What is Implicit Deep Learning?
Prediction rules in deep learning are based on a forward, recursive computation through several layers. Implicit deep learning rules go much beyond, by relying on the solution of an implicit (or, “fixed-point”) equation that has to be numerically solved in order to make the prediction: for... Read more
Watch: Imitation Learning: Reinforcement Learning For The Real World
This talk will introduce the formal Imitation Learning problem and discuss two main categories of agent training in the Imitation Learning paradigm: behavioral cloning and interactive experts. The talk will also include examples of where it could be used to solve real-world problems and a demonstration... Read more
Latest Developments in GANs
Generative adversarial networks (GANs) is a compelling technology that’s widely considered one of the most interesting developments in AI and deep learning in the past decade. This article provides an overview of the ODSC West 2018 talk “Latest Developments in GANs,” presented by Seth Weidman of... Read more
Model Evaluation in the Land of Deep Learning
Applications for machine learning and deep learning have become increasingly accessible. For example, Keras provides APIs with TensorFlow backend that enable users to build neural networks without being fluent with TensorFlow. Despite the ease of building and testing models, deep learning has suffered from a lack... Read more
Deep Learning in R with Keras
The primary professional hat I wear is as a data science consultant working with machine learning in a variety of problem domains. Due to my academic past in computer science and applied statistics, my development environment of choice today is typically R. Lately however, Python is... Read more
The Logistics of Starting Deep Learning
Deep learning models can be intimidating and rightfully so; in their raw form they are highly complex algorithms that need to be engineered with expertise. However, deep learning is very accessible to individuals with a background in technical skills thanks to organizations and individuals that have... Read more