- Deep-Q Learning Pong with TensorFlow and PyGame: http://www.danielslater.net/2016/03/deep-q-learning-pong-with-TensorFlow.html
- Must Know Tips/Tricks in Deep Neural Networks: http://lamda.nju.edu.cn/weixs/project/CNNTricks/CNNTricks.html
- Stanford CS231n: https://www.youtube.com/playlist?list=PLwQyV9I_3POsyBPRNUU_ryNfXzgfkiw2p
- Neural Doodle: https://github.com/alexjc/neural-doodle
- SigOpt for ML: Unsupervised Learning with Even Less Supervision Using Bayesian Optimization: http://blog.sigopt.com/post/140871698423/sigopt-for-ml-unsupervised-learning-with-even
- Montreal Deep Learning Summer School: https://sites.google.com/site/deeplearningsummerschool2016/
- The Sadness and Beauty of Watching Google’s AI Play Go: https://sites.google.com/site/deeplearningsummerschool2016/
- Low-Rank Passthrough Neural Networks: https://www.reddit.com/r/MachineLearning/comments/49yjry/160303116_lowrank_passthrough_neural_networks/
- Getting Started with MXNet: https://indico.io/blog/getting-started-with-mxnet/
- Deploy TensorFlow Graphs for Faster Evaluation and Export to TensorFlow-less Environments Running NumPy: https://github.com/riga/tfdeploy
- Value Iteration Networks: http://arxiv.org/pdf/1602.02867v1.pdf
- Collection of Machine Learning Interview Questions: http://analyticscosm.com/machine-learning-interview-questions-for-data-scientist-interview/
- Interview Experience with DeepMind: https://www.reddit.com/r/MachineLearning/comments/49rbnn/has_anyone_here_interviewed_with_deepmind_what/
- Train Your Own Image Classifier with Inception in TensorFlow: http://googleresearch.blogspot.kr/2016/03/train-your-own-image-classifier-with.html
- Comprehensive List of All of the Famous Problems Solved Successfully Using Deep Learning: https://www.reddit.com/r/MachineLearning/comments/49izzc/is_there_a_comprehensive_list_of_all_of_the/
- Deep Learning in a Nutshell: Sequence Learning: https://devblogs.nvidia.com/parallelforall/deep-learning-nutshell-sequence-learning/
- Learning Physical Intuition of Block Towers by Example: http://arxiv.org/abs/1603.01312
- Intuitive Explanation of Gaussian Processes: https://www.reddit.com/r/MachineLearning/comments/49elmx/can_someone_explain_gaussian_processes_intuitively/
- The DeepMind Bubble?: https://www.reddit.com/r/MachineLearning/comments/49bpid/the_deepmind_bubble/
- Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks: http://arxiv.org/abs/1603.01431
- Dynamic Memory Networks for Visual and Textual Question Answering: http://arxiv.org/abs/1603.01417