The focus of Deep Learning is currently on specific perceptual tasks, and there are many successes.
All classes start at 9am PT and will be recorded for later viewing.
|7/22||Class #1 – Introduction to Deep Learning (30 mins + Q&A) – Recording, Slides, Hands-on lab|
|7/29||Office Hours for Class #1 (1 hour of Q&A) – Recording, Slides, Q&A log|
|8/5||Class #2 – Getting Started with DIGITS interactive training system for image classification (30 mins + Q&A)Recording, Slides, Hands-on lab|
|8/12||Office Hours for Class #2 (1 hour of Q&A)|
|8/19||Class #3 – Getting Started with the Caffe Framework|
|8/26||Office Hours for Class #3|
|9/2||Class #4 – Getting Started with the Theano Framework|
|9/9||Office Hours for Class #4|
|9/16||Class #5 – Getting Started with the Torch Framework|
|9/23||Office Hours for Class #5|
Please send your questions to firstname.lastname@example.org before the Office Hours sessions, so the instructors can prepare helpful answers. You might even get a faster response!
The hands-on lab exercises for each class will be available at nvidia.qwiklab.com for free during the course.
More Deep Learning Courses
- Andrew Ng’s Coursera course provides a good introduction to deep learning (Coursera, YouTube)
- Yann LeCun’s NYU Course on Deep Learning, Spring 2014 (TechTalks)
- Geoffrey Hinton’s “Neural Networks for Machine Learning” course from Oct 2012 (Coursera)
- Rob Fergus’s “Deep Learning for Computer Vision” tutorial from NIPS 2013 (slides, video)
- Caltech’s introductory deep learning course taught by Yasser Abu-Mostafa (YouTube)
- Stanford CS224d: Deep Learning for Natural Language Processing (video, slides, tutorials)