Deep Learning Resources
Books:
- Deep Learning textbook, by Ian Goodfellow, Yoshua Bengio and Aaron Courville
- A Guide to Deep Learning , by YerevaNN research lab
- Introduction to Artificial Neural Networks and Deep Learning , by Sebastian Raschka
- Neural Networks and Deep Learning, by Michael Nielsen
- Theories of Deep Learning, by Stanford University
Blogs:
- Andrej Karpathy Deep Learning blog
- Montreal.AI
- Colah's Blog [Christopher Olah]
- WildML Blog [Denny Britz]
- Tim Dettmers Deep Learning blog
- Deep Learning resources , by Dr. Jeremy D. Jackson
- Sebastian Ruder Deep Learning blog
- Machine Learning Mastery
- Deep Learning blog
- Deep Learning Reading List
- Deep Learning, by Sebastian Raschka
- Unsupervised Feature Learning and Deep Learning Resources
- Nuit Blanche Deep Learning Blog
Open Courses for Deep Learning:
- CS231n: Convolutional Neural Networks for Visual Recognition, by A. Karpathy and Fei-Fei Li at Stanford
- DEEP LEARNING course, by François Fleuret, EPFL.
- Introduction to deep-learning
- Deep Learning courses, by Andrew Ng
- Neural Networks for Machine Learning, by Geoffrey Hinton
- Deep Learning for Self-Driving Cars, by MIT
- Introduction to Deep Learning, by MIT
- Practical Deep Learning For Coders, by fast.ai
- Deep Learning course, by Nvidia
- Deep Learning course, by Google at Udacity
- Deep Learning course, by Y. LeCun at the New York University
- Deep Learning for Natural Language Processing, by R. Socher at Stanford
- Machine Learning course, by N. de Freitas at Oxford
- Neural Networks course, by H. Larochelle at Université de Sherbrooke
- Topics Course on Deep Learning, by Joan Bruna at the Statistics Department of UC Berkeley
- Deep Reinforcement Learning, by Sergey Levine at UC Berkeley
- Deep Reinforcement Learning Bootcamp
- CMU Neural Nets for NLP 2017, by CMU
- Deep Learning Fundamentals, by DEEPLEARNING.TV
- The Deep Learning and Reinforcement Summer School in Montreal
- Tensorflow for Deep Learning Research, by Stanford University
- Tensorflow Dev Summit
- Deep Learning Courses
- CS230: Deep Learning Stanford course
Deep Learning Cheat Sheets:
- Deep Learning Cheat Sheets 1, by Robbie Allen
- Deep Learning Cheat Sheets 2, by Stefan Kojouharov
- Deep Learning Cheat Sheets 3 , by Kailash Ahirwar
- BASIC PATTERNS IN NEURAL NETWORKS, BY PLATFORM
- Victoria's ML Notes
Tutorials:
- The First Comprehensive Overview of AI for the General Public
- Seedbank: Collection of Interactive Machine Learning Examples
- Interactive Machine Learning list
- Learning deep architectures for AI (literature review on deep learning) , by Yoshua Bengio
- Cognitive Computational Neuroscience (CCN) 2017 videos
- Deep Neural Networks Introduction, By 3Blue1Brown
- ResNet in PyTorch, By Sudhanshu Passi
- Structured Learning and Prediction in Computer Vision tutorial , by Sebastian Nowozin and Christoph Lampert
- Reading lists for Deep Learning researchers , by MILA
- Reading on Deep Networks
- Deep Learning resources, by LISA
- Tutorial on Hardware Architectures for Deep Neural Networks
- Deep Learning Tutorials
- Deep Reinforcement Learning (RL) Tutorials
- The Neural Network Zoo
- Intro to Deep Learning with Python
- Deep Learning Papers Reading Roadmap
- Awesome Deep Learning
- Deep Learning Tutorial
- Deep Learning Made Simple , by Vivek Panyam
- Deep Learning Tutorial
- Feature Visualization
- TensorFlow for Poets Tutorial
- AI and Deep Learning in 2017 – A Year in Review
- Deep Learning in Medical Imaging resources
- DL resources list
- Key Papers in Deep RL
Datasets:
Deep Learning Papers:
Useful Libraries for Deep Learning:
- Popular Deep Learning Libraries, by Dr. Jason Brownlee
- DLTK (Deep Learning Tool-kit)
Deep Learning Project Ideas:
- Awesome Deep Learning Project Ideas
- CS229 Machine Learning Final Projects
- Stanford Machine Learning Group Projects
- CS231n: Convolutional Neural Networks for Visual Recognition course Projects
- Deep Learning Applications
- CS230: Deep Learning Projects