The focus of Deep Learning is currently on specific perceptual tasks, and there are many successes.
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- DEEP LEARNING APPROACH
Course Schedule
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 dl-course@nvidia.com 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)