This section is a collection of resources about Deep Learning

Deep Learning

Online Courses**

  • Geoffrey Hinton Neural Networks for Machine Learning (2012) : https://www.cs.toronto.edu/~hinton/coursera_lectures.html
  • Andrew Ng Deep Learning : https://www.coursera.org/specializations/deep-learning
  • FastAI Courses https://www.fast.ai/
  • UCL x Deepmind Lectures : https://www.youtube.com/playlist?list=PLqYmG7hTraZCDxZ44o4p3N5Anz3lLRVZF
  • NYU Deep Learning Lecture (Pytorch): https://atcold.github.io/pytorch-Deep-Learning/, https://www.youtube.com/playlist?list=PLLHTzKZzVU9eaEyErdV26ikyolxOsz6mq

Theory

  • Deep Learning (Goodfellow et al, 2017): https://www.deeplearningbook.org/

  • Grokking Deep Learning (Andrew Trask) : https://www.amazon.co.uk/Deep-Learning-Python-Francois-Chollet/dp/1617294438

Applications

  • Deep Learning with Python (Francois Chollet) : https://www.amazon.co.uk/Deep-Learning-Python-Francois-Chollet/dp/1617294438

Image Classification

InceptionV3

Natural Language Processing

Text Model

RNNs(Recurrent Neural Networks) RNNS & LSTMs (Long Short Term Memory)

Term Frequency - Inverse Document Frequency (Tf-Idf)

Word Embeddings

Sequence-to-Sequence Models

Attention

Transformers

Bidirectional Encoder Representations from Transformers (BERT)

Reinforcement Learning

Reinforcement Learning: An Introduction (Sutton & Barto, 2018): https://www.amazon.co.uk/Reinforcement-Learning-Introduction-Richard-Sutton/dp/0262039249

Novel Topics

  • CS 330: Deep Multi-Task and Meta Learning : https://cs330.stanford.edu/

Cognitive Computing

  • Probabilistic Models of Cognition : https://probmods.org/
  • NYU Computational cognitive modeling - Spring 2020: https://brendenlake.github.io/CCM-site/
20/06/2020