Concepts:

• Gradient Descend intuition
• Convolutional Neural Networks (CNN)
• Long-Short Term Memory networks
• Generative Adversarial Networks
• Variational Autoencoders
• Approaches to Natural Language Understanding
• Neural Network Architectures in Computer Vision

Courses:

• Neural Networks in Machine Learning: Geoffrey Hinton (Coursera)
• Convolutional Neural Networks for Visual Recognition (Stanford)
• Deep Learning for Natural Language Processing (Stanford)
• Deep learning: University of Oxford (2015) by Nando de Freitas

Infrastructure, frameworks, datasets, tools:

• Infrastructure for Deep Learning (OpenAI)
• Deep Learning Frameworks Compared
• Internet: A firehose of free labelled data

Other Resources (tutorials, blogs, YouTube channels):

• Learning Reinforcement Learning (with Code, Exercises and Solutions)
• Unsupervised Feature Learning and Deep Learning Tutorial (Stanford)
• Eugenio Culurciello's blog
• Grokking Deep Learning
• DeepLearning.TV

Research papers:

• Differentiable neural computers
• Density estimation using Real NVP
• Crypto-nets: Neural networks over encrypted data
• Learning to learn by gradient descent by gradient descent
• A Clockwork RNN

Research papers in computer vision (images / videos):

• PixelCNN + PixelRNN + PixelCNN 2.0
• Image Compression with Neural Networks
• Deep Neural Networks for YouTube Recommendations
• Unsupervised Learning for Physical Interaction through Video Prediction

Research papers in reinforcement learning:

• Dynamic Frame skip Deep Q Network
• Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering
• A2T: Attend, Adapt and Transfer: Adaptive Transfer Learning
• Learning to Poke by Poking: Experiential Learning of Intuitive Physics
• Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation

Research papers in natural language processing:

• Google's Neural Machine Translation System
• SPINN: Unified Parsing and Sentence Understanding
• A Neural Knowledge Language Model (August 2016)

Research papers in audio / speech:

• WaveNet: A Generative Model for Raw Audio

How you can contribute:

• Post summaries and intuitive explanations of things you read.
• Bonus points for summarizing the top research papers
• Discuss anything deep learning related
• Post links to implementations of research papers
• Post links to cool projects
• Write a review of a course you took or a lecture you watched
• Tell your friends about the community!