Deep Learning Resources

A curated list of deep learning resources books, courses, papers, libraries, conferences, sample code, and many more.

Table of Contents

• Free Books

• Courses

• Videos and Lectures

• Papers

• Tutorials

• Sample Code

• Datasets

• Conferences

• Libraries

Free Books

1. Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville
2. Deep Learning by Microsoft Research
3. Neural Networks and Deep Learning by Michael Nielsen
4. Neuraltalk by Andrej Karpathy

Courses

1. Neural Networks for Machine Learning
2. Neural networks class
3. Deep Learning Course
4. A.I - Berkeley
5. A.I - MIT
6. Convolutional Neural Networks for Visual Recognition - Stanford
7. Practical Deep Learning For Coders
8. MIT 6.S191 Introduction to Deep Learning

Videos and Lectures

1. Deep Learning, Self-Taught Learning and Unsupervised Feature Learning by Andrew Ng
2. Recent Developments in Deep Learning by Geoff Hinton
3. The Unreasonable Effectiveness of Deep Learning by Yann LeCun
4. Deep Learning of Representations by Yoshua bengio
5. Making Sense of the World with Deep Learning by Adam Coates
6. How Deep Neural Networks Work
7. MIT 6.S191 Introduction to Deep Learning

Papers

1. ImageNet Classification with Deep Convolutional Neural Networks
2. Using Very Deep Autoencoders for Content Based Image Retrieval
3. Learning Deep Architectures for AI
4. Neural Networks for Named Entity Recognition
5. Training tricks by YB

Tutorials

1. How to Implement the Backpropagation Algorithm From Scratch In Python
2. image classifier using convolutional neural network
3. A Beginner’s Guide to Recurrent Networks and LSTMs
4. Recurrent Neural Networks Tutorial, Part 1 – Introduction to RNNs
5. Stochastic Gradient Descent (SGD) with Python
6. A Guide to Deep Learning in PyTorch
7. A Quick Introduction to Neural Networks
8. An Intuitive Explanation of Convolutional Neural Networks

Sample Code

1. Deep Learning with Python
2. Deep Learning with TensorFlow
3. Fundamentals of Deep Learning
4. Introduction to Deep Learning Using R

Datasets

1. CIFAR-10 and CIFAR-100
2. Google House Numbers from street view
3. IMAGENET
4. MNIST Handwritten digits
5. Tiny Images 80 Million tiny images6.
6. Fashion-MNIST

Conferences

1. CVPR - IEEE Conference on Computer Vision and Pattern Recognition
2. AAMAS - International Joint Conference on Autonomous Agents and Multiagent Systems
3. IJCAI - International Joint Conference on Artificial Intelligence
4. NIPS - Neural Information Processing Systems
5. ICLR - International Conference on Learning Representations

Libraries

1. Tensorflow
2. Keras - A high-level neural networks API running on top of TensorFlow, CNTK, or Theano
3. Caffe
4. Torch7
5. Theano
6. MXnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning framework
7. TensorFlow.js - formerly known as deeplearn.js

Contributing

Jika anda ingin berkontribusi dalam github ini, sangat disarankan untuk Pull Request namun dengan resource berbahasa indonesia.