/Megalodon

Various ML/DL Resources organised at a single place.

MEGALODON: ML/DL Resources At One Place

Blogs Type Comments
Stanford NLP Research exposition
Berkeley AI Research Lab (BAIR) Research exposition
Off the Convex Path Research exposition
Andrej Karpathy blog, Andrej Karpathy - Medium Personal
Distill Research exposition
Christopher Olah Personal
Sebastian Ruder Personal
Elad Hazan Personal
Ben Recht Personal
Shakir Muhammed Personal
Inference.vc Personal
R2RT Personal
Pythonic Perambulations Personal
Sebastian Raschka Personal
Papers wih Code
Depth First Learning
Moritz Hardt
MadryLab
Podcasts/Talks Type Comments
Talking Machines Interviews/Research Exposition
Radim Interviews
The AI Podcast Interviews
TWiML & AI Interviews
NLP-Highlights Interviews
The Thesis Review Interviews
NLP with Friends Presentations
ML Street Talk Interviews
Pytorch-dev-podcast Talks Pytorch Internals
Stanford MLSys Seminar Talks
Books Focus Areas Comments
Pattern Recognition and Machine Learning      MATLAB Code
Machine Learning: A Probabilistic Perspective
Deep Learning
The Elements of Statistical Learning
Computer Age Statistical Inference
Foundations of Machine Learning
Understanding Machine Learning: From Theory to Algorithms
Probabilistic Graphical Models
Information Theory, Inference and Learning Algorithms
Model Based Machine Learning
Neural Networks for Pattern Recognition
Foundations Of Data Science Lectures
A Course in Machine Learning
Monographs/Reports/Tutorials Focus Areas Comments
Algorithmic Aspects Of ML Videos
Non Convex Optimization for ML
NMT AND Seq2Seq Models: A Tutorial
Intro to ML without Deep Learning
Frontiers in Massive Data Analysis
High-Dimensional Data Analysis: Curses & Blessings 50 years of Data Science
Summer Schools/Seminars Focus Areas Comments
MLSS, Tubingen 07
Cambridge
MLSS Purdue
DLSS, Montreal 2015
DLSS, Montreal 2016
Deep Learning School, 2016 All Videos
DLSS & RLSS, Montreal 2017
MLSS, Kioloa 08
MLSS, Chicago 09
MLSS, Canberra 02
MSR India MLSS, 2015
AI Summer School, 2017
Deep RL Bootcamp, Berkeley
IPAM Deep Learning, Feature Learning, 2012
MLSS, Max Plank Institute, 2017
MLSS, CMU 2014
Deep Learning: Theory, Algorithms, and Applications
Gaussian Process Summer Schools
MLSS, Iceland, 2014
MLSS Sydney 15
MLSS London 2019
New Tech in Math Seminar
Video Channels/Videos Focus Areas Comments
videolectures.net ICLR 2016
Channel9 NIPS 16
TechTalks.tv EMNLP 16, ACL 16, ICML 2016
Deep Learning Book Club Deep learning book club
Simons Institute DL Tutorials, Opt & Fairness
Center for Brains, Minds and Machines (CBMM)
CVF
CIS Lectures
ICLR 2015
IAS, Theoretical ML
Formal and Applied Linguistics
ICLR 19
David MacKay's Lectures
ACL 2019
Allen AI
General Resource Curations Type Comments
ML Videos
Scholarpedia
Short Science
Best Papers
Pluralsight
Safari Books Online
Specialized Resource Curations Type Comments
Meta-Learning Papers
NLP Tasks
Academic Groups/Labs Focus Areas Comments
Saarland
UFLDL
Industry Groups/Labs Focus Areas Comments
Microsoft
Microsoft Maluuba
Google Brain
Facebook
Google Deepmind
Apple
Recast AI NLP & Dialog Management API Reference
Salesforce Einstein
Courses Institute Comments
Tensorfow for DL Research General: Advanced Scientific computing
Intro to AI, UCB
CNN for Visual Recognition
Deep Learning for NLP
Intro to Deep Learning, Princeton
Intro to Deep Learning, MIT
NN for ML
Stanford ML (Old), Current
Probabilistic Graphical Models    
Fast.AI
Oxford Deep NLP, 17
Theories of deep learning Videos
Deep Learning System
PGM Flexible models of uncertainty
Frameworks/Libraries Type Comments
Tensorfow TF Dev Summit, 17
Theano
Lasagne
Keras
CNTK
MXNET
Torch
PyTorch
Caffe
Caffe2
Chainer
DyNet
DL4J
Scikit-learn
MALMO RL Environment
OpenAI Gym RL Environments Not sure if still actively developed
Gluon
ConvNetJS
deeplearn.js
Tangent Source to Source
Autograd Torch-Autograd
Interviews Focus Area Comments
Deep Learning Heroes
Social Networks Type Comments
Twitter
Reddit Go to place for ml
Hacker News
Deep Learning Study Group, SF
Newsletters Focus Areas Comments
Wild Week in AI 2017 review
NLP News
the morning paper
ML Review
Import AI
Gitxiv Newsletter
Nathan Benaich
O'reilly AI Newsletter
Inside AI
Videolectures Digest
Datasets Task Comments
NLP Datasets

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