└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # My Artificial Intelligence Bookmarks [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome) 2 | Curated list of my reads, implementations and core concepts of Artificial Intelligence, Deep Learning, Machine Learning by best folk in the world. 3 | 4 | ## 🎉🎉🎉 Purchase updated list here --> [AI Bookmarks](https://aibookmarks.carrd.co/) 5 | 6 | ## 2018-2019 7 | -

4 Sequence Encoding Blocks You Must Know Besides RNN/LSTM in Tensorflow · Han Xiao Tech Blog - Deep Learning, Tensorflow, Machine Learning and more! 70 | -

Automated front-end development using deep learning 71 | -

A New Angle on L2 Regularization 72 | -

Another Datum 73 | -

IML-Sequence 74 | -

ml4a-guides/q_learning.ipynb at experimental · ml4a/ml4a-guides 75 | -

tensorflow-without-a-phd/00_RNN_predictions_playground.ipynb at master · GoogleCloudPlatform/tensorflow-without-a-phd 76 | -

Convolutional Neural Network based Image Colorization using OpenCV | Learn OpenCV 77 | -

Transfer Learning in NLP – Feedly Blog 78 | -

CS 229 - Deep Learning Cheatsheet 79 | -

Google AI Blog: Introducing a New Framework for Flexible and Reproducible Reinforcement Learning Research 80 | -

Building a text classification model with TensorFlow Hub and Estimators 81 | -

Deploy TensorFlow models – Towards Data Science 82 | -

Deep Learning – Mohit Jain 83 | -

Анализ тональности текстов с помощью сверточных нейронных сетей / Блог компании Mail.Ru Group / Хабр 84 | -

Machine Reading Comprehension Part II: Learning to Ask & Answer · Han Xiao Tech Blog - Deep Learning, Tensorflow, Machine Learning and more! 85 | -

How to Quickly Train a Text-Generating Neural Network for Free 86 | -

Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code 87 | -

More Effective Transfer Learning for NLP 88 | -

Machine Learning using Google Cloud ML Engine. – Gautam Karmakar – Medium 89 | -

Training and Serving ML models with tf.keras – TensorFlow – Medium 90 | -

How to deploy TensorFlow models to production using TF Serving 91 | -

Playing Mortal Kombat with TensorFlow.js. Transfer learning and data augmentation · Minko Gechev's blog 92 | -

Beyond Interactive: Notebook Innovation at Netflix – Netflix TechBlog – Medium 93 | -

Mask R-CNN with OpenCV - PyImageSearch 94 | -

The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) – Jay Alammar – Visualizing machine learning one concept at a time 95 | -

Serving ML Quickly with TensorFlow Serving and Docker 96 | -

Human-Centered AI 97 | -

Keras as a simplified interface to TensorFlow: tutorial 98 | -

Serving Google BERT in Production using Tensorflow and ZeroMQ · Han Xiao Tech Blog - Deep Learning, NLP, AI 99 | -

Multilingual Sentence Embeddings for Zero-Shot Transfer – Applying a Single Model on 93 Languages | Lyrn.AI 100 | -

Deploy flask app with nginx using gunicorn and supervisor 101 | -

Dept. of Computer Sci.: Module Handbook for the Bachelor and Master Programmes 102 | -

14 NLP Research Breakthroughs You Can Apply To Your Business 103 | -

The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) – Jay Alammar – Visualizing machine learning one concept at a time 104 | -

A gallery of interesting Jupyter Notebooks · jupyter/jupyter Wiki 105 | -

CS294-158 Deep Unsupervised Learning Spring 2018 106 | -

Object Detection in Google Colab with Custom Dataset 107 | -

Advanced Visualization for Data Scientists with Matplotlib 108 | -

FavioVazquez/ds-cheatsheets: List of Data Science Cheatsheets to rule the world 109 | -

Gentle Dive into Math Behind Convolutional Neural Networks 110 | -

Customer churn prediction in telecom using machine learning in big data platform 111 | -

How to Port-Forward Jupyter Notebooks – Scott Hawley – Development Blog 112 | -

Top 8 trends from ICLR 2019 113 | -

The Illustrated Word2vec – Jay Alammar – Visualizing machine learning one concept at a time 114 | -

Google AI Blog: Transformer-XL: Unleashing the Potential of Attention Models 115 | -

TensorFlow & reflective tape : why I’m bad at basketball 🏀 116 | -

Topic Modeling with LSA, PLSA, LDA & lda2Vec 117 | -

GAN — Some cool applications of GANs. – Jonathan Hui – Medium 118 | -

A Recipe for Training Neural Networks 119 | -

Practice Quantum Computing | Brilliant 120 | -

dennybritz/reinforcement-learning: Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course. 121 | -

Weight Agnostic Neural Networks 122 | -

Transformers from scratch | Peter Bloem 123 | -

The Illustrated Transformer – Jay Alammar – Visualizing machine learning one concept at a time 124 | -

The Illustrated GPT-2 (Visualizing Transformer Language Models) – Jay Alammar – Visualizing machine learning one concept at a time 125 | -

ml-dl - 126 | -

Indaba2019 NLP Talk.pdf - Google Drive 127 | -

Automation via Reinforcement Learning 128 | -

CS 224N | Home 129 | -

mihail911/nlp-library: curated collection of papers for the nlp practitioner 📖👩‍🔬 130 | -

Production-ready Docker images 131 | -

The key lessons from “Where Good Ideas Come From” by Steven Johnson 132 | -

Neural Networks Example, Math and code – Brian Omondi Asimba 133 | -

How to apply machine learning and deep learning methods to audio analysis 134 | -

A Visual Guide to Using BERT for the First Time – Jay Alammar – Visualizing machine learning one concept at a time 135 | -

NeurIPS · SlidesLive 136 | -

https://towardsdatascience.com/from-pre-trained-word-embeddings-to-pre-trained-language-models-focus-on-bert-343815627598 137 | -

Joel Grus – Fizz Buzz in Tensorflow 138 | -

(160) Visual Interpretability of CNNs | Himanshu Rawlani | PyData Pune Meetup | July 2019 - YouTube 139 | -

Memo's Island: A simple and interpretable performance measure for a binary classifier 140 | -

Data-Science-Periodic-Table.pdf 141 | -

Writing a Generic TensorFlow Serving Client for Tensorflow Serving models 142 | -

Writing a Generic TensorFlow Serving Client for Tensorflow Serving models 143 | -

dspace.mit.edu/bitstream/handle/1721.1/41487/AI_WP_316.pdf 144 | -

Transformers are Graph Neural Networks | NTU Graph Deep Learning Lab 145 | -

7 advanced pandas tricks for data science - Towards Data Science 146 | -

Google AI Blog: XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization 147 | -

CNN Explainer 148 | -

Polo Club of Data Science @ Georgia Tech: Human-Centered AI, Deep Learning Interpretation & Visualization, Cybersecurity, Large Graph Visualization and Mining | Georgia Tech | Atlanta, GA 30332, United States 149 | -

Sara Robinson 150 | -

Common statistical tests are linear models (or: how to teach stats) 151 | -

Zero-Shot Learning for Text Classification 152 | 153 | ## 2015 - 2018 154 | 155 | -

Python Deep Learning Projects 156 | -

Deep Learning 157 | 158 | -

Fast Artificial Neural Network Library (FANN) 159 | -

The Nature of Code 160 | -

Create and Train Custom Neural Network Architectures - MATLAB & Simulink - MathWorks India 161 | -

limdu js framework 162 | -

Neural networks and deep learning 163 | -

NN Why Does it Work? 164 | -

Introduction to Convex Optimization | Electrical Engineering and Computer Science | MIT OpenCourseWare 165 | -

Python Programming Tutorials imge recognition 166 | -

Data Science and Machine Learning Essentials | edX 167 | -

Deep learning – Convolutional neural networks and feature extraction with Python | Pyevolve 168 | -

50 external machine learning / data science resources and articles - Data Science Central 169 | -

Hacker's guide to Neural Networks 170 | -

Fast Forward Labs: How do neural networks learn? 171 | -

Machine Learning 172 | -

Memkite – Deep Learning for iOS (tested on iPhone 6S), tvOS and OS X developed in Metal and Swift | Memkite 173 | -

Demis Hassabis, CEO, DeepMind Technologies - The Theory of Everything | Machine Learning & Computer Vision Talks 174 | -

DataTau- hacker news on DL 175 | -

Deeplearning4j - Open-source, distributed deep learning for the JVM 176 | -

Torch | Recurrent Model of Visual Attention 177 | -

Machine Learning for Developers by Mike de Waard 178 | -

Deep Learning - Community - Google+ 179 | -

A Tour of Machine Learning Algorithms - Data Science Central 180 | -

Understanding Natural Language with Deep Neural Networks Using Torch | Parallel Forall 181 | -

What a Deep Neural Network thinks about your #selfie 182 | -

Jason Yosinski 183 | -

WildML | A blog about Machine Learning, Deep Learning and NLP. 184 | -

Getting Started — TensorFlow 185 | -

Deep Learning:Theoretical Motivations - VideoLectures.NET 186 | -

Unsupervised Feature Learning and Deep Learning Tutorial 187 | -

Wit — Getting Started 188 | -

research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf 189 | -

ujjwalkarn/Machine-Learning-Tutorials 190 | -

Top 10 Machine Learning APIs: AT&T Speech, IBM Watson, Google Prediction | ProgrammableWeb 191 | -

NeuroVis | An interactive introduction to neural networks 192 | -

learning_tensorflow/word2vec.md at master · chetannaik/learning_tensorflow 193 | -

intro2deeplearning/notebooks at master · rouseguy/intro2deeplearning 194 | -

Autoencoders - Ep. 10 (Deep Learning SIMPLIFIED) - YouTube 195 | -

Python Programming Tutorials 196 | -

How to Prepare Data For Machine Learning - Machine Learning Mastery 197 | -

Solve Machine Learning Problems Step-by-Step - Machine Learning Mastery 198 | -

Implementing a CNN for Text Classification in TensorFlow – WildML 199 | -

Anyone Can Learn To Code an LSTM-RNN in Python (Part 1: RNN) - i am trask 200 | -

7 Steps to Mastering Machine Learning With Python 201 | -

DeepLearningKit – Open Source Deep Learning Framework for Apple’s iOS, OS X and tvOS | Open Source Deep Learning Framework for iOS, OS X and tvOS 202 | -

A Visual Introduction to Machine Learning 203 | -

Attention and Memory in Deep Learning and NLP – WildML 204 | -

A Neural Network in 11 lines of Python (Part 1) - i am trask 205 | -

Python Training | Python For Data Science | Learn Python 206 | -

Understanding LSTM Networks -- colah's blog 207 | -

deeplearning4nlp-tutorial/2015-10_Lecture at master · nreimers/deeplearning4nlp-tutorial 208 | -

Collection Of 51 Free eBooks On Python Programming 209 | -

Analyzing 50k fonts using deep neural networks | Erik Bernhardsson 210 | -

Data Science Ontology 211 | -

Reddit Machine Learning 212 | -

RNNs in Darknet 213 | -

caesar0301/awesome-public-datasets: An awesome list of high-quality open datasets in public domains (on-going). 214 | -

A Beginner's Guide to Recurrent Networks and LSTMs - Deeplearning4j: Open-source, distributed deep learning for the JVM 215 | -

Essentials of Machine Learning Algorithms (with Python and R Codes) 216 | -

PythonForArtificialIntelligence - Python Wiki 217 | -

carpedm20/lstm-char-cnn-tensorflow: LSTM language model with CNN over characters in TensorFlow 218 | -

kjw0612/awesome-rnn: Recurrent Neural Network - A curated list of resources dedicated to RNN 219 | -

sherjilozair/char-rnn-tensorflow: Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow 220 | -

Stanford University CS231n: Convolutional Neural Networks for Visual Recognition 221 | -

Top Youtube Videos On Machine Learning, Neural Network & Deep Learning 222 | -

The Spectator ← Shakir's Machine Learning Blog 223 | -

Preprocessing text data — Computational Statistics in Python 0.1 documentation 224 | -

Tutorial : Beginner to advanced machine learning in 15 hour Videos – AnalyticsPro : Analytics Tutorials for Data Science , BI & Big Data 225 | -

Next Big Future: Recurrent Neural Nets 226 | -

Must Know Tips/Tricks in Deep Neural Networks - Data Science Central 227 | -

Visual Question Answering Demo in Python Notebook – Aaditya Prakash (Adi) – Random Musings of Computer Vision grad student 228 | -

A Neural Network Playground 229 | -

Machine Learning : Few rarely shared trade secrets - Data Science Central 230 | -

Russell Stewart- debug NN 231 | -

Extracting meaningful content from raw HTML – Thomas Uhrig 232 | -

Russell Stewart 233 | -

Recurrent Neural Networks | The Shape of Data 234 | -

ITP-NYU - Spring 2016 235 | -

White Rain Noise Generator | White Noise & Rain Combined 236 | -

Machine Learning 237 | -

A GloVe implementation in Python - foldl 238 | -

Understanding Convolution in Deep Learning - Tim Dettmers 239 | -

The Chars74K image dataset - Character Recognition in Natural Images 240 | -

A Statistical View of Deep Learning (IV): Recurrent Nets and Dynamical Systems ← The Spectator 241 | -

Tensorflow and deep learning - without a PhD - Google Slides 242 | -

Parity problem, sequential: 1 bit at a time 243 | -

Machine learning with Python: A Tutorial 244 | -

Neural networks and deep learning 245 | -

Juergen Schmidhuber's home page - Universal Artificial Intelligence - New AI - Deep Learning - Recurrent Neural Networks - Computer Vision - Object Detection - Image segmentation - Goedel Machine - Theory of everything - Algorithmic theory of everything - 246 | -

t-SNE – Laurens van der Maaten 247 | -

Stanford University CS224d: Deep Learning for Natural Language Processing 248 | -

Machine Learning 10-701/15-781: Lectures 249 | -

Word2vec Tutorial | RaRe Technologies 250 | -

Machine learning | 251 | -

How to read: Character level deep learning – Offbit 252 | -

Generative Models 253 | -

goodrahstar/python-machine-learning-book: The "Python Machine Learning" book code repository and info resource 254 | -

A noob’s guide to implementing RNN-LSTM using Tensorflow — Medium 255 | -

Structuring Your TensorFlow Models 256 | -

Would You Survive the Titanic? A Guide to Machine Learning in Python - SocialCops Blog 257 | -

Berkeley AI Materials 258 | -

Hello, TensorFlow! - O'Reilly Media 259 | -

Visualize Algorithms based on the Backpropagation — NeuPy 260 | -

Talking Machines 261 | -

Probability Cheatsheet 262 | -

A Beginner's Guide To Understanding Convolutional Neural Networks – Adit Deshpande – CS Undergrad at UCLA ('19) 263 | -

Approaching (Almost) Any Machine Learning Problem | Abhishek Thakur | No Free Hunch 264 | -

MNE — MNE 0.12.0 documentation 265 | -

Alexandre Gramfort - Telecom ParisTech 266 | -

Image Kernels explained visually 267 | -

Introduction to Recurrent Networks in TensorFlow 268 | -

The Ultimate List of TensorFlow Resources: Books, Tutorials & More - Hacker Lists 269 | -

the morning paper | an interesting/influential/important paper from the world of CS every weekday morning, as selected by Adrian Colyer 270 | -

The Ultimate List of TensorFlow Resources: Books, Tutorials & More - Hacker Lists 271 | -

ChristosChristofidis/awesome-deep-learning: A curated list of awesome Deep Learning tutorials, projects and communities. 272 | -

Nervana's Deep Learning Course - Nervana 273 | -

CNN practical 274 | -

What my deep model doesn't know... | Yarin Gal - Blog | Cambridge Machine Learning Group 275 | -

TensorFlow Linear Model Tutorial 276 | -

tensorflow/models · GitHub 277 | -

An introduction to Generative Adversarial Networks (with code in TensorFlow) - AYLIEN 278 | -

Neural Network Evolution Playground with Backprop NEAT | 大トロ 279 | -

Teaching an AI to write Python code with Python code • Will cars dream? 280 | -

GitHub - paarthneekhara/text-to-image: Tensorflow implementation of text to image synthesis using thought vectors 281 | -

Learning TensorFlow 282 | -

The 9 Deep Learning Papers You Need To Know About (Understanding CNNs Part 3) – Adit Deshpande – CS Undergrad at UCLA ('19) 283 | -

What is the Role of the Activation Function in a Neural Network? 284 | -

Research paper categorization using machine learning and NLP 285 | -

WaveNet: A Generative Model for Raw Audio | DeepMind 286 | -

Backpropagation In Convolutional Neural Networks - DeepGrid 287 | -

Urban Sound Classification 288 | -

Model evaluation, model selection, and algorithm selection in machine learning - Part II 289 | -

Data - Melbourne University AES/MathWorks/NIH Seizure Prediction | Kaggle 290 | -

cchio/deep-pwning: Metasploit for machine learning. 291 | -

First Contact With TensorFlow | Professor Jordi Torres | UPC & BSC-CNS | Barcelona 292 | -

Industry // AETROS 293 | -

alrojo/tensorflow-tutorial · GitHub 294 | -

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow — Mourad Mourafiq 295 | -

Python Programming Tutorials 296 | -

Natural Language Processing and Voice Recognition Resources – Niaw de Leon 297 | -

Deep Learning for Beginners 298 | -

TensorFlow on Android - O'Reilly Media 299 | -

TensorFlow for Mobile Poets « Pete Warden's blog 300 | -

5 algorithms to train a neural network | Neural Designer 301 | -

Hello DeepQ — koaning.io 302 | -

How do Convolutional Neural Networks work? 303 | -

Neural Network Architectures 304 | -

Question-Answer Dataset 305 | -

Image-to-Image Translation with Conditional Adversarial Networks 306 | -

GitXiv: Collaborative Open Computer Science 307 | -

Deep Learning Cheat Sheet 308 | -

Introduction to Recurrent Networks in TensorFlow 309 | -

DmitryUlyanov/neural-style-audio-tf · GitHub 310 | -

goodrahstar/tensorflow-value-iteration-networks: TensorFlow implementation of the Value Iteration Networks (NIPS '16) paper 311 | -

Recurrent Neural Network Tutorial for Artists | 大トロ 312 | -

Eric Jang: Summary of NIPS 2016 313 | -

GitHub - thtrieu/essence: AutoDiff DAG builder, built from scratch on top of numpy and C 314 | -

Deep Text Correcter 315 | -

GitHub - zhongwen/predictron: Tensorflow implementation of "The Predictron: End-To-End Learning and Planning" 316 | -

The major advancements in Deep Learning in 2016 - Tryolabs Blog 317 | -

Contact Me – the data science blog 318 | -

Wikipedia Monolingual Corpora | linguatools 319 | -

Tensorflow RNN-LSTM implementation to count number of set bits in a binary string 320 | -

buriburisuri/speech-to-text-wavenet: Speech-to-Text-WaveNet : End-to-end sentence level English speech recognition based on DeepMind's WaveNet and tensorflow 321 | -

AudioSet 322 | -

The amazing power of word vectors | the morning paper 323 | -

Let’s Make A Bot That Applies To Jobs For Us With Python – Millennial Dave 324 | -

goodrahstar/pytorch-tutorial: tutorial for researchers to learn deep learning with pytorch. 325 | -

Overview - seq2seq 326 | -

Baidu Deep Voice explained: Part 1 — the Inference Pipeline 327 | -

Tensorflow demystified – gk_ – Medium 328 | -

Transfer Learning - Machine Learning's Next Frontier 329 | -

Deep Learning with Emojis (not Math) – tech-at-instacart 330 | -

Anything2Vec, or How Word2Vec Conquered NLP – Yves Peirsman 331 | -

Q/A System — Deep learning(2/2) – Becoming Human – Medium 332 | -

A Brief History of CNNs in Image Segmentation: From R-CNN to Mask R-CNN 333 | -

Face recognition with Keras and OpenCV – Above Intelligent (AI) 334 | -

A16Z AI Playbook 335 | -

Neural Text Embeddings for Information Retrieval (WSDM 2017) 336 | -

A list of artificial intelligence tools you can use today — for personal use (1/3) 337 | -

Research Blog: The Machine Intelligence Behind Gboard 338 | -

paraphrase-id-tensorflow/README.md at master · nelson-liu/paraphrase-id-tensorflow 339 | -

NeuroNER/README.md at master · Franck-Dernoncourt/NeuroNER 340 | -

Generative Adversarial Networks for Beginners - O'Reilly Media 341 | -

Neural Translation of Musical Style 342 | -

Deep-Learning-Papers-Reading-Roadmap/README.md at master · songrotek/Deep-Learning-Papers-Reading-Roadmap 343 | -

AI Progress Measurement | Electronic Frontier Foundation 344 | -

How to Visualize Your Recurrent Neural Network with Attention in Keras 345 | -

Deep adversarial learning is finally ready 🚀 and will radically change the game 346 | -

Franck-Dernoncourt/NeuroNER: Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results. 347 | -

Serving Tensorflow 348 | -

How To Install and Use Docker on Ubuntu 16.04 | DigitalOcean 349 | -

Jupyter + Tensorflow + Nvidia GPU + Docker + Google Compute Engine 350 | -

TensorForce: A TensorFlow library for applied reinforcement learning - reinforce.io 351 | -

Exploring LSTMs 352 | -

Perform sentiment analysis with LSTMs, using TensorFlow - O'Reilly Media 353 | -

Robust Adversarial Examples 354 | -

Learning to Learn – The Berkeley Artificial Intelligence Research Blog 355 | -

My Curated List of AI and Machine Learning Resources from Around the Web 356 | -

goodrahstar/headlines: Automatically generate headlines to short articles 357 | -

Deep Learning for NLP Best Practices 358 | -

facebookresearch/DrQA: Reading Wikipedia to Answer Open-Domain Questions 359 | -

Q/A System — Deep learning(2/2) – Becoming Human 360 | -

Contextual Chatbots with Tensorflow – Chatbots Magazine 361 | -

Text-Clustering-API/CLAAS_public.py at master · vivekkalyanarangan30/Text-Clustering-API 362 | -

tensorflow/nmt: TensorFlow Neural Machine Translation Tutorial 363 | -

Cutting Edge Deep Learning for Coders—Launching Deep Learning Part 2 · fast.ai 364 | -

facebookresearch/end-to-end-negotiator: Deal or No Deal? End-to-End Learning for Negotiation Dialogues 365 | -

examples/main.py at master · pytorch/examples 366 | -

BotCube/awesome-bots: A curated awesome list of resources from the bots/AI world by BotCube team. Join our newsletter to get five epic actionable bot tricks delivered to your inbox once a week! 🤖 ❤️ 367 | -

Thushv » Word2Vec (Part 1): NLP With Deep Learning with Tensorflow (Skip-gram) 368 | -

Tensorflow-Programs-and-Tutorials/Question Pair Classification with RNNs.ipynb at master · adeshpande3/Tensorflow-Programs-and-Tutorials 369 | -

Intro Deep Learning for Chatbots, Part 2 | Open Data Science 370 | -

Named Entity Recognition and the Road to Deep Learning 371 | -

Building Convolutional Neural Networks with Tensorflow – Ahmet Taspinar 372 | -

Visualising Activation Functions in Neural Networks - dashee87.github.io 373 | -

Deep RL Bootcamp - Lectures 374 | -

Tensorflow Text Classification - Python Deep Learning - Source Dexter 375 | -

my-deity/COMPRESSION_CUM_CLASSIFICATION_v_2.ipynb at master · akanimax/my-deity 376 | -

“TensorBoard - Visualize your learning.” 377 | -

Cyborg Writer 378 | -

Data For Everyone Library | CrowdFlower 379 | -

loretoparisi/CapsNet: CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules" 380 | -

TFX: A TensorFlow-based production scale machine learning platform | the morning paper 381 | -

Flair of Machine Learning 382 | -

Recurrent-Highway-Hypernetworks-NIPS/README.md at master · jsuarez5341/Recurrent-Highway-Hypernetworks-NIPS · GitHub 383 | -

Using Artificial Intelligence to Augment Human Intelligence 384 | -

Learning from Imbalanced Classes - Silicon Valley Data Science 385 | -

Regular Expressions for Data Scientists 386 | -

Google Developers Blog: Introducing TensorFlow Feature Columns 387 | -

bharathgs/Awesome-pytorch-list: A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc. 388 | -

Gaussian Processes – EFavDB 389 | -

Neural Smithing 390 | -

Hooks Data says… 391 | -

Introduction to Various Reinforcement Learning Algorithms. Part I (Q-Learning, SARSA, DQN, DDPG) 392 | -

Introduction to Python Ensembles 393 | -

Data Science Summit 2018 394 | -

facebookresearch/Detectron · GitHub 395 | -

GitHub - openai/gradient-checkpointing: Make huge neural nets fit in memory 396 | -

Deep-Learning/Skip-Grams-Solution.ipynb at master · priya-dwivedi/Deep-Learning · GitHub 397 | -

Recurrent Neural Networks for Drawing Classification | TensorFlow 398 | -

2017 news - Gwern.net 399 | -

How neural networks are trained 400 | -

GitHub - huseinzol05/Emotion-Classification-Comparison: Classification comparison between various models and learning on emotion datasets 401 | -

mil-tokyo/webdnn: The Fastest DNN Running Framework on Web Browser 402 | -

Beautiful.AI - AI Powered Presentations 403 | -

Stanford DAWN Deep Learning Benchmark (DAWNBench) · 404 | -

Introduction to Learning to Trade with Reinforcement Learning – WildML 405 | -

Play with Kubernetes 406 | -

Deep Reinforcement Learning Doesn't Work Yet 407 | -

Release 0.5.0 · PAIR-code/deeplearnjs · GitHub 408 | -

Teaching RL 409 | -

Introducing the Uber AI Residency 410 | -

The Matrix Calculus You Need For Deep Learning 411 |

412 | 413 | 414 | 415 | ----- 416 | ### Contributing 417 | Have anything in mind that you think is awesome and would fit in this list? Feel free to send a [pull request](https://github.com/goodrahstar/my-awesome-AI-bookmarks/pulls). 418 | 419 | ----- 420 | ## License 421 | 422 | [![CC0](http://i.creativecommons.org/p/zero/1.0/88x31.png)](http://creativecommons.org/publicdomain/zero/1.0/) 423 | 424 | To the extent possible under law, [Rahul Kumar](http://www.hellorahulk.com) has waived all copyright and related or neighboring rights to this work. 425 | 426 | --------------------------------------------------------------------------------