vyraun / Megalodon
Various ML/DL Resources organised at a single place.
Stars: ✭ 189
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MEGALODON: ML/DL Resources At One Place
👉 Raise a pull request to add content/comments & make this list more useful or to remove anything.
| 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 | Type | Comments |
|---|---|---|
| Talking Machines | Interviews/Research Exposition | |
| Radim | Interviews | |
| The AI Podcast | Interviews | |
| TWiML & AI | Interviews | |
| NLP-Highlights | Interviews |
| 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 | ||
| Google Deepmind | ||
| Apple | ||
| Recast AI | NLP & Dialog Management | API Reference |
| Salesforce Einstein |
| 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 |
|---|---|---|
| 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 |
Other Blogs
- https://smerity.com/articles/articles.html
- http://veredshwartz.blogspot.in/
- https://stats385.github.io/blogs
- https://blogs.princeton.edu/imabandit/
- https://www.countbayesie.com
- http://building-babylon.net/
- While My MCMC Gently Samples
- http://www.marekrei.com/blog/online-representation-learning-in-recurrent-neural-language-models/
- http://mlg.eng.cam.ac.uk/yarin/blog.html
- https://blogs.msdn.microsoft.com/ericlippert/
- https://ericlippert.com/
- https://blogs.msdn.microsoft.com/ericlippert/tag/high-dimensional-spaces/
- http://blog.echen.me/
- radford neal's blog https://radfordneal.wordpress.com/
- http://timvieira.github.io/blog/archives.html
- http://p.migdal.pl/
- https://www.quora.com/What-are-the-best-machine-learning-blogs-or-resources-available
- http://ml.typepad.com/machine_learning_thoughts/
- https://jmetzen.github.io/
- http://peekaboo-vision.blogspot.in/
- http://sebastianruder.com/word-embeddings-1/index.html?utm_content=bufferca13e&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
- https://jamesmccaffrey.wordpress.com/
- http://alexey.radul.name/2/
- https://www.reddit.com/r/MachineLearning/comments/4juw5z/cool_deep_learning_ml_blogs/
- http://dsnotes.com/
- http://mccormickml.com/
- http://approximatelycorrect.com/
- http://timdettmers.com/2015/03/26/convolution-deep-learning/
- https://campus2.acm.org/public/qj/brandingqj/xrds.cfm
- http://www.kemaswill.com/
- https://jacobgil.github.io/
- http://www.argmin.net/
- http://tscholak.github.io/
- https://theneuralperspective.com/
- https://devblogs.nvidia.com/parallelforall/
- http://textminingonline.com/
- http://douglasduhaime.com/blog/clustering-semantic-vectors-with-python
- https://telecombcn-dl.github.io/2017-dlcv/
- cs 231 http://cs231n.stanford.edu/, cs 221 http://web.stanford.edu/class/cs221/
- http://nlpforhackers.io/
- Keras, Torch, TF, http://dp.readthedocs.io/en/latest/index.html , Theano blogs are also very useful.
- http://gkalliatakis.com/blog/delving-deep-into-gans
- https://oshearesearch.com/
- https://www.youtube.com/watch?v=Xogn6veSyxA&list=PLbwivfGkPdvi4Pn66Yc8TWpNy18OhEhW_
- https://terrytao.wordpress.com/2017/03/01/special-cases-of-shannon-entropy/
- http://nlp.yvespeirsman.be/
- http://bcomposes.com/2015/11/26/simple-end-to-end-tensorflow-examples/
- https://prateekvjoshi.com/
- http://anie.me/
- http://wellredd.uk/
- http://p.migdal.pl/2017/04/30/teaching-deep-learning.html
- https://www.countbayesie.com/blog/2017/5/9/kullback-leibler-divergence-explained
- https://vkrakovna.wordpress.com/
- https://codingmachinelearning.wordpress.com/
- http://www.seaandsailor.com/index.html
- http://www.kentran.net/
- http://arogozhnikov.github.io/
- http://philipperemy.github.io/
- http://appliedpredictivemodeling.com/blog/2014/11/27/08ks7leh0zof45zpf5vqe56d1sahb0
- http://andymiller.github.io/blog/
- http://www.argmin.net/
- http://setosa.io/ev/
- http://rbharath.github.io/
- http://wiseodd.github.io/
- https://www.neurolab.de/cosine_notes.html
- http://willwolf.io/
- http://www.minimizingregret.com/
- http://bookworm.benschmidt.org/index.html
- http://www.brainyblog.net/
- https://iksinc.wordpress.com/
- https://erikbern.com/
- https://kevinzakka.github.io/2016/07/13/k-nearest-neighbor/
- http://dustintran.com/blog/
- http://blog.kaggle.com/
- http://jponttuset.cat/blog/
- http://blog.echen.me/2017/05/30/exploring-lstms/
- http://deliprao.com/archives/187
- http://www.ams.org/samplings/feature-column/fcarc-svd
- https://www.countbayesie.com/all-posts/
- http://briandolhansky.com/blog/2013/7/8/ml-primers
- http://iamtrask.github.io/
- https://hips.seas.harvard.edu/blog/
- https://jeremykun.com/
- https://theclevermachine.wordpress.com/
- http://nlp.yvespeirsman.be/blog/
- http://andrew.gibiansky.com/
- https://joanna-bryson.blogspot.de/
- http://tullo.ch/
- http://yanran.li/
- https://theneural.wordpress.com/
- http://jotterbach.github.io/archive/
- http://ischlag.github.io/
- http://www.marekrei.com/blog/
- http://alexhwilliams.info/itsneuronalblog/
- http://planspace.org/
- https://shapeofdata.wordpress.com/page/2/
- https://machinethoughts.wordpress.com/
- http://shubhanshu.com/blog/
- https://gmarti.gitlab.io/
- http://www.panderson.me/blog/
- http://giorgiopatrini.org/posts/2017/09/06/in-search-of-the-missing-signals/
- http://www-users.cs.umn.edu/~verma/blog.html
- https://www.papernot.fr/en/blog
- https://gab41.lab41.org/
- http://blog.smola.org/
- http://mogren.one/blog/
- http://www.alexirpan.com/ good batchnorm
- https://machinethoughts.wordpress.com/
- http://deepdish.io/page3/
- https://github.com/ml4a ml for artists
- https://severelytheoretical.wordpress.com/
- https://codingmachinelearning.wordpress.com
- https://kratzert.github.io/openlearning
- https://recast.ai/
- https://www.techemergence.com/artificial-intelligence-podcast/
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