- CVPR18: Tutorial: Software Engineering in Computer Vision Systems
- CVPR18: Tutoral: Part 2: Software Engineering in Computer Vision Systems
- Machine Learning and the Market for Intelligence, 2017
- Machine Learning and the Market for Intelligence, 2016
- Jake VanderPlas The Python Visualization Landscape PyCon 2017
- Pycon 2016
- Jake Vanderplas - Statistics for Hackers - PyCon 2016.mp4
- Kinds of Intelligence Symposium at NIPS
- Metalearning
- Nips all videos
- Reprogramming the Human Genome With Artificial Intelligence - Brendan Frey - NIPS 2017
- Pieter Abbeel
- Deep RL
- test of time: Ali Rahimi
- notes on NIPS 2017
- RECURRENT NEURAL NETWORKS
- History of Bayesian Neural Networks (Keynote talk)
- Reliable Machine Learning in the Wild - NIPS 2016 Workshop
- Generative Adversarial Networks, Ian Goodfelow
- videos and slides
The talks at the Deep Learning School on September 24/25, 2016 were amazing. I clipped out individual talks from the full live streams and provided links to each below in case that's useful for people who want to watch specific talks several times (like I do). Please check out the official website(http://www.bayareadlschool.org) and full live streams below.
Having read, watched, and presented deep learning material over the past few years, I have to say that this is one of the best collection of introductory deep learning talks I've yet encountered. Here are links to the individual talks and the full live streams for the two days:
- Foundations of Deep Learning (Hugo Larochelle, Twitter
- Deep Learning for Computer Vision (Andrej Karpathy, OpenAI)
- Deep Learning for Natural Language Processing (Richard Socher, Salesforce)
- TensorFlow Tutorial (Sherry Moore, Google Brain)
- Foundations of Unsupervised Deep Learning (Ruslan Salakhutdinov, CMU)
- Nuts and Bolts of Applying Deep Learning (Andrew Ng)
- Deep Reinforcement Learning (John Schulman, OpenAI)
- Theano Tutorial (Pascal Lamblin, MILA)
- Deep Learning for Speech Recognition (Adam Coates, Baidu)
- Torch Tutorial (Alex Wiltschko, Twitter)
- Sequence to Sequence Deep Learning (Quoc Le, Google)
- Foundations and Challenges of Deep Learning (Yoshua Bengio)
Full Day Live Streams: Day 1 Day 2
Go to link for more information on the event, speaker bios, slides, etc. Huge thanks to the organizers (Shubho Sengupta et al) for making this event happen.
- Yan Lecun, Stockholm 2018
- Addressing Multithreading & Multiprocessing in Transparent & Pythonic Methods | SciPy 2018 | David L
- Intel AI Devcon 2018
- Building the Software 2.0 Stack by Andrej Karpathy from Tesla
- sysML Conference 2018
- Theoretical Machine Learning Lecture Series: How Could Machines Learn as Efficiently as Animals and Humans?
- Alena Kruchkova
- Google's DeepMind CEO: Future & Capabilities of Artificial Intelligence (AI)
- Yan Lecun National Taiwan Uni
- Yan LeCun, Obstacles to AI, Mathematical and Otherwise
- What Kaggle has learned from almost a million data scientists - Anthony Goldbloom (Kaggle)
- 2017-03-23 Yann LeCun-Deep Learning And The Future Of AI@Tsinghua University
- Deep Learning Practicals
- A DARPA Perspective on Artificial Intelligence
- TensorFlow Dev Summit 2017 - Livestream
- Andrew Ng: Artificial Intelligence is the New Electricity
- YanLecun, Edinburg 2017
- George Hotz Presents Comma Neo
- OpenCV for Embedded: Lessons Learned," a Presentation from Intel
- Practical Deep Learning For Coders
- NIPS 2016 Spotlight Videos
- Deep Learning and the Future of AI | Yann LeCun
- Stanford course, Andrej Karpathy, CS231n Winter 2016
- MICCAI 2016
- Data Science Summit 2016
- NVIDIA GTC DC Keynotes Day One
- NVIDIA GTC DC Keynote - Day Two
- NVIDIA GTS Talks
- funny AI video for Yan Lecun
- RI Seminar: Yann LeCun, Carnegie Mellon University
- Deep learning TV
- From Facebook AI research - Soumith Chintala - Adversarial Networks
- Import Keras in Deep Learning4J