Slides for classes taught by Adi
|Lecture 1||Neural Networks and Deep Learning||Google Slides|
|Lecture 2||Convolutional Neural Networks||Google Slides|
|Lecture 3||Recurrent Neural Networks||Google Slides|
|Lecture 4||Object localization and detection||Google Slides|
|Lecture 5||Generative Adversarial Networks||Google Slides|
|Lecture 6||Semantic Perceptual Image Compression||Google Slides|
|Lecture 7||Neural Networks with Memory||Google Slides|
Other presentations by Adi on Deep Learning
- General purpose GPU Computing and CUDA - Nov 30, 2015
- RNN, LSTM, NTM, GRU, RMVA, OMG !! - Nov 18, 2015
- Value of a feature - October 19, 2015
- Why CNN works - October 7, 2015
- Deeper inside CNN - September 29, 2015
- Inside CNN - September 16, 2015
- Deep Learning and CNN - February 22, 2016
(Very basics of Deep learning and CNN, meant as a gentle introduction to the field)
- Neural Networks and Deep Learning - May 2, 2016
- Visual Question Answering - August 12, 2016
Reading Material (Highly recommeded)
- Part 1: Nonlinear Classifiers and The Backpropagation Algorithm
- Part 2: Autoencoders, Convolutional Neural Networks and Recurrent Neural Networks
Deep Learning References
- UVA Deep Learning course. Contains easy to follow class video lectures, covers most of deep learning.
- CS231n: Convolutional Neural Networks for Visual Recognition Covers CNN only but in depth.
- Deep Learning. Very thorough and well written book. Covers almost everything.
- Neural Networks and Deep Learning. Light reading, only 6 chapters, easy to follow.
- Machine Learning. For better understanding of ML concepts, easy to follow.