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How Computers Learn

This Vienna Gödel Lecture provides a fascinating talk by Peter Norvig, Research Director at Google Inc. in the field of intelligent computers. Norvig talks about his long experience in AI and Machine Learning. The talk explains how computers learn from examples and what are the promises and limitations of these techniques.

Operationalizing Data Science

In the video presentation below, Joel Horwitz, Vice President, Partnerships, Digital Business Group for IBM Analytics, discusses what it means to “operationalize data science” – basically what it means to harden the ops behind running data science platforms.

Why Machine Learning Algorithms Fall Short

The video presentation below is “Why Machine Learning Algorithms Fall Short (And What You Can Do About It)” by Jean-François Puget, speaking at MLconf SF 2016. The talk examines how to overcome challenges in creating self-learning systems that perform better and are built to stand the test of time.

Deep Learning, Language and Cognition

In this public lecture at the Institute for Advanced Study, Christopher Manning, Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and Computer Science, discusses some of the results in deep learning with respect to computer vision, speech, and language.

Machines: How Do They Learn and Where Are They Headed?

In this public lecture held at the Institute for Advanced Study on October 27, 2017, Sanjeev Arora, Visiting Professor in the School of Mathematics, and Richard Zemel, Visitor in the School of Mathematics, gave brief talks about the field of machine learning and its major technical challenges. A panel discussion moderated by Robbert Dijkgraaf, Director and Leon Levy Professor, followed.

Things You Can Do with a Recurrent Neural Network

In this video presentation from the Linux.conf.au 2015 in Auckland, New Zealand, Douglas Bagnall examines a particularly hot topic in deep learning, namely recurrent neural networks, and all the things you can do with them.

Large Scale Deep Learning with TensorFlow

In this video presentation from the Spark Summit 2016 conference in San Francisco, Google’s Jeff Dean examines large scale deep learning with the TensorFlow framework. Jeff joined Google in 1999 and is currently a Google Senior Fellow.

Visualizing and Understanding Deep Neural Networks

In the video presentation below, Matthew Zeiler, PhD, Founder and CEO of Clarifai Inc, speaks about large convolutional neural networks. These networks have recently demonstrated impressive object recognition performance making real world applications possible. However, there was no clear understanding of why they perform so well, or how they might be improved.

Deep Learning – Theory and Applications

The video presentation below, “Deep Learning – Theory and Applications” is from the July 23rd SF Machine Learning Meetup at the Workday Inc. San Francisco office. The featured speaker is Ilya Sutskever who received his Ph.D. in 2012 from the University of Toronto working with deep learning luminary Geoffrey Hinton.

“Deep Learning” Book Chapter Walk-Throughs by Ian Goodfellow

Here’s a tremendous learning resource for Deep Learning practitioners – a complete set of video walk-through presentations for each chapter from the recent book “Deep Learning” by Goodfellow, Bengio, and Courville. This book is considered one of the finest texts on the subject. The video series is an excellent way to advance through all the material in the book.