My Artificial Intelligence Bookmarks

Curated list of my reads, implementations and core concepts of Artificial Intelligence, Deep Learning, Machine Learning by best folk in the world.

🎉🎉🎉 Purchase updated list here --> AI Bookmarks

2018-2019

• How to use transfer learning and fine-tuning in Keras and Tensorflow to build an image recognition…
• How to deploy Machine Learning models with TensorFlow. Part 1 — make your model ready for serving.
• image-classification-indoors-outdoors/image-classification.ipynb at master · manena/image-classification-indoors-outdoors
• (620) Learning to Communicate with Deep Multi-Agent Reinforcement Learning - Jakob Foerster - YouTube
• Compressing deep neural nets
• Engineering Extreme Event Forecasting at Uber with Recurrent Neural Networks - Uber Engineering Blog
• Run python script from init.d
• Daemon vs Upstart for python script - Stack Overflow
• Reinforcement learning for complex goals, using TensorFlow - O'Reilly Media
• Blockchains: How They Work and Why They’ll Change the World - IEEE Spectrum
• NET292.profile.indd
• GANs are Broken in More than One Way: The Numerics of GANs
• (74) Stanford Seminar - "Deep Learning for Dummies" Carey Nachenberg of Symantec and UCLA CS - YouTube
• Fast.ai: What I Learned from Lessons 1–3 – Hacker Noon
• Meet Horovod: Uber's Open Source Distributed Deep Learning Framework
• Home · cat /var/log/life
• 2D & 3D Visualization using NCE Cost | Kaggle
• New Theory Cracks Open the Black Box of Deep Learning | Quanta Magazine
• Feature Visualization
• Face It – The Artificially Intelligent Hairstylist | Intel® Software
• What is TensorFlow? | Opensource.com
• Estimating an Optimal Learning Rate For a Deep Neural Network – Medium
• Understanding Hinton’s Capsule Networks. Part I: Intuition.
• Capsule Networks Are Shaking up AI — Here’s How to Use Them
• Research Blog: Eager Execution: An imperative, define-by-run interface to TensorFlow
• Google and Uber’s Best Practices for Deep Learning – Intuition Machine – Medium
• TFX: A TensorFlow-based production scale machine learning platform | the morning paper
• Comprehensive data exploration with Python | Kaggle
• An Easy Guide to build new TensorFlow Datasets and Estimator with Keras Model | DLology
• Distributed TensorFlow: A Gentle Introduction
• Google Developers Blog: Introduction to TensorFlow Datasets and Estimators
• Google Developers Blog: Introducing TensorFlow Feature Columns
• TensorLy: Tensor learning in Python
• Question answering with TensorFlow - O'Reilly Media
• Kubernetes + GPUs 💙 Tensorflow – Intuition Machine – Medium
• Welcoming the Era of Deep Neuroevolution - Uber Engineering Blog
• Deep Learning for NLP, advancements and trends in 2017 - Tryolabs Blog
• Turning Design Mockups Into Code With Deep Learning - FloydHub Blog
• AI and Deep Learning in 2017 – A Year in Review – WildML
• Research Blog: The Google Brain Team — Looking Back on 2017 (Part 1 of 2)
• Reinforcement Learning · Artificial Inteligence
• Sketching Interfaces – Airbnb Design
• Machine Learning Explained: Understanding Supervised, Unsupervised, and Reinforcement Learning - Data Science Central
• Fine-tuning Convolutional Neural Network on own data using Keras Tensorflow – CV-Tricks.com
• A neural approach to relational reasoning | DeepMind
• Deep Reinforcement Learning Doesn't Work Yet
• Big Picture: Google Visualization Research
• Research Blog: Using Evolutionary AutoML to Discover Neural Network Architectures
• Secure Computations as Dataflow Programs - Cryptography and Machine Learning
• Teach Machine to Comprehend Text and Answer Question with Tensorflow - Part I · Han Xiao Tech Blog
• Deep Reinforcement Learning: Pong from Pixels
• Tensorboard on gcloud
• Entity extraction using Deep Learning based on Guillaume Genthial work on NER
• Deep Learning Book Notes, Chapter 3 (part 1): Introduction to Probability
• Predicting physical activity based on smartphone sensor data using CNN + LSTM
• Learn Word2Vec by implementing it in tensorflow – Towards Data Science
• TutorialBank: Learning NLP Made Easier - Alexander R. Fabbri
• How to Quickly Train a Text-Generating Neural Network for Free
• Code2Pix - Deep Learning Compiler for Graphical User Interfaces
• naacl18.pdf
• Deep Learning for Object Detection: A Comprehensive Review
• 4 Sequence Encoding Blocks You Must Know Besides RNN/LSTM in Tensorflow · Han Xiao Tech Blog - Deep Learning, Tensorflow, Machine Learning and more!
• Automated front-end development using deep learning
• A New Angle on L2 Regularization
• Another Datum
• IML-Sequence
• ml4a-guides/q_learning.ipynb at experimental · ml4a/ml4a-guides
• tensorflow-without-a-phd/00_RNN_predictions_playground.ipynb at master · GoogleCloudPlatform/tensorflow-without-a-phd
• Convolutional Neural Network based Image Colorization using OpenCV | Learn OpenCV
• Transfer Learning in NLP – Feedly Blog
• CS 229 - Deep Learning Cheatsheet
• Google AI Blog: Introducing a New Framework for Flexible and Reproducible Reinforcement Learning Research
• Building a text classification model with TensorFlow Hub and Estimators
• Deploy TensorFlow models – Towards Data Science
• Deep Learning – Mohit Jain
• Анализ тональности текстов с помощью сверточных нейронных сетей / Блог компании Mail.Ru Group / Хабр
• Machine Reading Comprehension Part II: Learning to Ask & Answer · Han Xiao Tech Blog - Deep Learning, Tensorflow, Machine Learning and more!
• How to Quickly Train a Text-Generating Neural Network for Free
• Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code
• More Effective Transfer Learning for NLP
• Machine Learning using Google Cloud ML Engine. – Gautam Karmakar – Medium
• Training and Serving ML models with tf.keras – TensorFlow – Medium
• How to deploy TensorFlow models to production using TF Serving
• Playing Mortal Kombat with TensorFlow.js. Transfer learning and data augmentation · Minko Gechev's blog
• Beyond Interactive: Notebook Innovation at Netflix – Netflix TechBlog – Medium
• Mask R-CNN with OpenCV - PyImageSearch
• The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) – Jay Alammar – Visualizing machine learning one concept at a time
• Serving ML Quickly with TensorFlow Serving and Docker
• Human-Centered AI
• Keras as a simplified interface to TensorFlow: tutorial
• Serving Google BERT in Production using Tensorflow and ZeroMQ · Han Xiao Tech Blog - Deep Learning, NLP, AI
• Multilingual Sentence Embeddings for Zero-Shot Transfer – Applying a Single Model on 93 Languages | Lyrn.AI
• Deploy flask app with nginx using gunicorn and supervisor
• Dept. of Computer Sci.: Module Handbook for the Bachelor and Master Programmes
• 14 NLP Research Breakthroughs You Can Apply To Your Business
• The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) – Jay Alammar – Visualizing machine learning one concept at a time
• A gallery of interesting Jupyter Notebooks · jupyter/jupyter Wiki
• CS294-158 Deep Unsupervised Learning Spring 2018
• Object Detection in Google Colab with Custom Dataset
• Advanced Visualization for Data Scientists with Matplotlib
• FavioVazquez/ds-cheatsheets: List of Data Science Cheatsheets to rule the world
• Gentle Dive into Math Behind Convolutional Neural Networks
• Customer churn prediction in telecom using machine learning in big data platform
• How to Port-Forward Jupyter Notebooks – Scott Hawley – Development Blog
• Top 8 trends from ICLR 2019
• The Illustrated Word2vec – Jay Alammar – Visualizing machine learning one concept at a time
• Google AI Blog: Transformer-XL: Unleashing the Potential of Attention Models
• TensorFlow & reflective tape : why I’m bad at basketball 🏀
• Topic Modeling with LSA, PLSA, LDA & lda2Vec
• GAN — Some cool applications of GANs. – Jonathan Hui – Medium
• A Recipe for Training Neural Networks
• Practice Quantum Computing | Brilliant
• 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.
• Weight Agnostic Neural Networks
• Transformers from scratch | Peter Bloem
• The Illustrated Transformer – Jay Alammar – Visualizing machine learning one concept at a time
• The Illustrated GPT-2 (Visualizing Transformer Language Models) – Jay Alammar – Visualizing machine learning one concept at a time
• ml-dl -
• Indaba2019 NLP Talk.pdf - Google Drive
• Automation via Reinforcement Learning
• CS 224N | Home
• mihail911/nlp-library: curated collection of papers for the nlp practitioner 📖👩‍🔬
• Production-ready Docker images
• The key lessons from “Where Good Ideas Come From” by Steven Johnson
• Neural Networks Example, Math and code – Brian Omondi Asimba
• How to apply machine learning and deep learning methods to audio analysis
• A Visual Guide to Using BERT for the First Time – Jay Alammar – Visualizing machine learning one concept at a time
• NeurIPS · SlidesLive
• https://towardsdatascience.com/from-pre-trained-word-embeddings-to-pre-trained-language-models-focus-on-bert-343815627598
• Joel Grus – Fizz Buzz in Tensorflow
• (160) Visual Interpretability of CNNs | Himanshu Rawlani | PyData Pune Meetup | July 2019 - YouTube
• Memo's Island: A simple and interpretable performance measure for a binary classifier
• Data-Science-Periodic-Table.pdf
• Writing a Generic TensorFlow Serving Client for Tensorflow Serving models
• Writing a Generic TensorFlow Serving Client for Tensorflow Serving models
• dspace.mit.edu/bitstream/handle/1721.1/41487/AI_WP_316.pdf
• Transformers are Graph Neural Networks | NTU Graph Deep Learning Lab
• 7 advanced pandas tricks for data science - Towards Data Science
• Google AI Blog: XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
• CNN Explainer
• 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
• Sara Robinson
• Common statistical tests are linear models (or: how to teach stats)
• Zero-Shot Learning for Text Classification

2015 - 2018

• Python Deep Learning Projects
• Deep Learning
• Fast Artificial Neural Network Library (FANN)
• The Nature of Code
• Create and Train Custom Neural Network Architectures - MATLAB & Simulink - MathWorks India
• limdu js framework
• Neural networks and deep learning
• NN Why Does it Work?
• Introduction to Convex Optimization | Electrical Engineering and Computer Science | MIT OpenCourseWare
• Python Programming Tutorials imge recognition
• Data Science and Machine Learning Essentials | edX
• Deep learning – Convolutional neural networks and feature extraction with Python | Pyevolve
• 50 external machine learning / data science resources and articles - Data Science Central
• Hacker's guide to Neural Networks
• Fast Forward Labs: How do neural networks learn?
• Machine Learning
• Memkite – Deep Learning for iOS (tested on iPhone 6S), tvOS and OS X developed in Metal and Swift | Memkite
• Demis Hassabis, CEO, DeepMind Technologies - The Theory of Everything | Machine Learning & Computer Vision Talks
• DataTau- hacker news on DL
• Deeplearning4j - Open-source, distributed deep learning for the JVM
• Torch | Recurrent Model of Visual Attention
• Machine Learning for Developers by Mike de Waard
• Deep Learning - Community - Google+
• A Tour of Machine Learning Algorithms - Data Science Central
• Understanding Natural Language with Deep Neural Networks Using Torch | Parallel Forall
• What a Deep Neural Network thinks about your #selfie
• Jason Yosinski
• WildML | A blog about Machine Learning, Deep Learning and NLP.
• Getting Started — TensorFlow
• Deep Learning:Theoretical Motivations - VideoLectures.NET
• Unsupervised Feature Learning and Deep Learning Tutorial
• Wit — Getting Started
• research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf
• ujjwalkarn/Machine-Learning-Tutorials
• Top 10 Machine Learning APIs: AT&T Speech, IBM Watson, Google Prediction | ProgrammableWeb
• NeuroVis | An interactive introduction to neural networks
• learning_tensorflow/word2vec.md at master · chetannaik/learning_tensorflow
• intro2deeplearning/notebooks at master · rouseguy/intro2deeplearning
• Autoencoders - Ep. 10 (Deep Learning SIMPLIFIED) - YouTube
• Python Programming Tutorials
• How to Prepare Data For Machine Learning - Machine Learning Mastery
• Solve Machine Learning Problems Step­-by­-Step - Machine Learning Mastery
• Implementing a CNN for Text Classification in TensorFlow – WildML
• Anyone Can Learn To Code an LSTM-RNN in Python (Part 1: RNN) - i am trask
• 7 Steps to Mastering Machine Learning With Python
• 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
• A Visual Introduction to Machine Learning
• Attention and Memory in Deep Learning and NLP – WildML
• A Neural Network in 11 lines of Python (Part 1) - i am trask
• Python Training | Python For Data Science | Learn Python
• Understanding LSTM Networks -- colah's blog
• deeplearning4nlp-tutorial/2015-10_Lecture at master · nreimers/deeplearning4nlp-tutorial
• Collection Of 51 Free eBooks On Python Programming
• Analyzing 50k fonts using deep neural networks | Erik Bernhardsson
• Data Science Ontology
• Reddit Machine Learning
• RNNs in Darknet
• caesar0301/awesome-public-datasets: An awesome list of high-quality open datasets in public domains (on-going).
• A Beginner's Guide to Recurrent Networks and LSTMs - Deeplearning4j: Open-source, distributed deep learning for the JVM
• Essentials of Machine Learning Algorithms (with Python and R Codes)
• PythonForArtificialIntelligence - Python Wiki
• carpedm20/lstm-char-cnn-tensorflow: LSTM language model with CNN over characters in TensorFlow
• kjw0612/awesome-rnn: Recurrent Neural Network - A curated list of resources dedicated to RNN
• sherjilozair/char-rnn-tensorflow: Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow
• Stanford University CS231n: Convolutional Neural Networks for Visual Recognition
• Top Youtube Videos On Machine Learning, Neural Network & Deep Learning
• The Spectator ← Shakir's Machine Learning Blog
• Preprocessing text data — Computational Statistics in Python 0.1 documentation
• Tutorial : Beginner to advanced machine learning in 15 hour Videos – AnalyticsPro : Analytics Tutorials for Data Science , BI & Big Data
• Next Big Future: Recurrent Neural Nets
• Must Know Tips/Tricks in Deep Neural Networks - Data Science Central
• Visual Question Answering Demo in Python Notebook – Aaditya Prakash (Adi) – Random Musings of Computer Vision grad student
• A Neural Network Playground
• Machine Learning : Few rarely shared trade secrets - Data Science Central
• Russell Stewart- debug NN
• Extracting meaningful content from raw HTML – Thomas Uhrig
• Russell Stewart
• Recurrent Neural Networks | The Shape of Data
• ITP-NYU - Spring 2016
• White Rain Noise Generator | White Noise & Rain Combined
• Machine Learning
• A GloVe implementation in Python - foldl
• Understanding Convolution in Deep Learning - Tim Dettmers
• The Chars74K image dataset - Character Recognition in Natural Images
• A Statistical View of Deep Learning (IV): Recurrent Nets and Dynamical Systems ← The Spectator
• Tensorflow and deep learning - without a PhD - Google Slides
• Parity problem, sequential: 1 bit at a time
• Machine learning with Python: A Tutorial
• Neural networks and deep learning
• 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 -
• t-SNE – Laurens van der Maaten
• Stanford University CS224d: Deep Learning for Natural Language Processing
• Machine Learning 10-701/15-781: Lectures
• Word2vec Tutorial | RaRe Technologies
• Machine learning |
• How to read: Character level deep learning – Offbit
• Generative Models
• goodrahstar/python-machine-learning-book: The "Python Machine Learning" book code repository and info resource
• A noob’s guide to implementing RNN-LSTM using Tensorflow — Medium
• Structuring Your TensorFlow Models
• Would You Survive the Titanic? A Guide to Machine Learning in Python - SocialCops Blog
• Berkeley AI Materials
• Hello, TensorFlow! - O'Reilly Media
• Visualize Algorithms based on the Backpropagation — NeuPy
• Talking Machines
• Probability Cheatsheet
• A Beginner's Guide To Understanding Convolutional Neural Networks – Adit Deshpande – CS Undergrad at UCLA ('19)
• Approaching (Almost) Any Machine Learning Problem | Abhishek Thakur | No Free Hunch
• MNE — MNE 0.12.0 documentation
• Alexandre Gramfort - Telecom ParisTech
• Image Kernels explained visually
• Introduction to Recurrent Networks in TensorFlow
• The Ultimate List of TensorFlow Resources: Books, Tutorials & More - Hacker Lists
• the morning paper | an interesting/influential/important paper from the world of CS every weekday morning, as selected by Adrian Colyer
• The Ultimate List of TensorFlow Resources: Books, Tutorials & More - Hacker Lists
• ChristosChristofidis/awesome-deep-learning: A curated list of awesome Deep Learning tutorials, projects and communities.
• Nervana's Deep Learning Course - Nervana
• CNN practical
• What my deep model doesn't know... | Yarin Gal - Blog | Cambridge Machine Learning Group
• TensorFlow Linear Model Tutorial
• tensorflow/models · GitHub
• An introduction to Generative Adversarial Networks (with code in TensorFlow) - AYLIEN
• Neural Network Evolution Playground with Backprop NEAT | 大トロ
• Teaching an AI to write Python code with Python code • Will cars dream?
• GitHub - paarthneekhara/text-to-image: Tensorflow implementation of text to image synthesis using thought vectors
• Learning TensorFlow
• The 9 Deep Learning Papers You Need To Know About (Understanding CNNs Part 3) – Adit Deshpande – CS Undergrad at UCLA ('19)
• What is the Role of the Activation Function in a Neural Network?
• Research paper categorization using machine learning and NLP
• WaveNet: A Generative Model for Raw Audio | DeepMind
• Backpropagation In Convolutional Neural Networks - DeepGrid
• Urban Sound Classification
• Model evaluation, model selection, and algorithm selection in machine learning - Part II
• Data - Melbourne University AES/MathWorks/NIH Seizure Prediction | Kaggle
• cchio/deep-pwning: Metasploit for machine learning.
• First Contact With TensorFlow | Professor Jordi Torres | UPC & BSC-CNS | Barcelona
• Industry // AETROS
• alrojo/tensorflow-tutorial · GitHub
• Sequence prediction using recurrent neural networks(LSTM) with TensorFlow — Mourad Mourafiq
• Python Programming Tutorials
• Natural Language Processing and Voice Recognition Resources – Niaw de Leon
• Deep Learning for Beginners
• TensorFlow on Android - O'Reilly Media
• TensorFlow for Mobile Poets « Pete Warden's blog
• 5 algorithms to train a neural network | Neural Designer
• Hello DeepQ — koaning.io
• How do Convolutional Neural Networks work?
• Neural Network Architectures
• Question-Answer Dataset
• Image-to-Image Translation with Conditional Adversarial Networks
• GitXiv: Collaborative Open Computer Science
• Deep Learning Cheat Sheet
• Introduction to Recurrent Networks in TensorFlow
• DmitryUlyanov/neural-style-audio-tf · GitHub
• goodrahstar/tensorflow-value-iteration-networks: TensorFlow implementation of the Value Iteration Networks (NIPS '16) paper
• Recurrent Neural Network Tutorial for Artists | 大トロ
• Eric Jang: Summary of NIPS 2016
• GitHub - thtrieu/essence: AutoDiff DAG builder, built from scratch on top of numpy and C
• Deep Text Correcter
• GitHub - zhongwen/predictron: Tensorflow implementation of "The Predictron: End-To-End Learning and Planning"
• The major advancements in Deep Learning in 2016 - Tryolabs Blog
• Contact Me – the data science blog
• Wikipedia Monolingual Corpora | linguatools
• Tensorflow RNN-LSTM implementation to count number of set bits in a binary string
• buriburisuri/speech-to-text-wavenet: Speech-to-Text-WaveNet : End-to-end sentence level English speech recognition based on DeepMind's WaveNet and tensorflow
• AudioSet
• The amazing power of word vectors | the morning paper
• Let’s Make A Bot That Applies To Jobs For Us With Python – Millennial Dave
• goodrahstar/pytorch-tutorial: tutorial for researchers to learn deep learning with pytorch.
• Overview - seq2seq
• Baidu Deep Voice explained: Part 1 — the Inference Pipeline
• Tensorflow demystified – gk_ – Medium
• Transfer Learning - Machine Learning's Next Frontier
• Deep Learning with Emojis (not Math) – tech-at-instacart
• Anything2Vec, or How Word2Vec Conquered NLP – Yves Peirsman
• Q/A System — Deep learning(2/2) – Becoming Human – Medium
• A Brief History of CNNs in Image Segmentation: From R-CNN to Mask R-CNN
• Face recognition with Keras and OpenCV – Above Intelligent (AI)
• A16Z AI Playbook
• Neural Text Embeddings for Information Retrieval (WSDM 2017)
• A list of artificial intelligence tools you can use today — for personal use (1/3)
• Research Blog: The Machine Intelligence Behind Gboard
• paraphrase-id-tensorflow/README.md at master · nelson-liu/paraphrase-id-tensorflow
• NeuroNER/README.md at master · Franck-Dernoncourt/NeuroNER
• Generative Adversarial Networks for Beginners - O'Reilly Media
• Neural Translation of Musical Style
• Deep-Learning-Papers-Reading-Roadmap/README.md at master · songrotek/Deep-Learning-Papers-Reading-Roadmap
• AI Progress Measurement | Electronic Frontier Foundation
• How to Visualize Your Recurrent Neural Network with Attention in Keras
• Deep adversarial learning is finally ready 🚀 and will radically change the game
• Franck-Dernoncourt/NeuroNER: Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
• Serving Tensorflow
• How To Install and Use Docker on Ubuntu 16.04 | DigitalOcean
• Jupyter + Tensorflow + Nvidia GPU + Docker + Google Compute Engine
• TensorForce: A TensorFlow library for applied reinforcement learning - reinforce.io
• Exploring LSTMs
• Perform sentiment analysis with LSTMs, using TensorFlow - O'Reilly Media
• Robust Adversarial Examples
• Learning to Learn – The Berkeley Artificial Intelligence Research Blog
• My Curated List of AI and Machine Learning Resources from Around the Web
• goodrahstar/headlines: Automatically generate headlines to short articles
• Deep Learning for NLP Best Practices
• facebookresearch/DrQA: Reading Wikipedia to Answer Open-Domain Questions
• Q/A System — Deep learning(2/2) – Becoming Human
• Contextual Chatbots with Tensorflow – Chatbots Magazine
• Text-Clustering-API/CLAAS_public.py at master · vivekkalyanarangan30/Text-Clustering-API
• tensorflow/nmt: TensorFlow Neural Machine Translation Tutorial
• Cutting Edge Deep Learning for Coders—Launching Deep Learning Part 2 · fast.ai
• facebookresearch/end-to-end-negotiator: Deal or No Deal? End-to-End Learning for Negotiation Dialogues
• examples/main.py at master · pytorch/examples
• 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! 🤖 ❤️
• Thushv » Word2Vec (Part 1): NLP With Deep Learning with Tensorflow (Skip-gram)
• Tensorflow-Programs-and-Tutorials/Question Pair Classification with RNNs.ipynb at master · adeshpande3/Tensorflow-Programs-and-Tutorials
• Intro Deep Learning for Chatbots, Part 2 | Open Data Science
• Named Entity Recognition and the Road to Deep Learning
• Building Convolutional Neural Networks with Tensorflow – Ahmet Taspinar
• Visualising Activation Functions in Neural Networks - dashee87.github.io
• Deep RL Bootcamp - Lectures
• Tensorflow Text Classification - Python Deep Learning - Source Dexter
• my-deity/COMPRESSION_CUM_CLASSIFICATION_v_2.ipynb at master · akanimax/my-deity
• “TensorBoard - Visualize your learning.”
• Cyborg Writer
• Data For Everyone Library | CrowdFlower
• loretoparisi/CapsNet: CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules"
• TFX: A TensorFlow-based production scale machine learning platform | the morning paper
• Flair of Machine Learning
• Recurrent-Highway-Hypernetworks-NIPS/README.md at master · jsuarez5341/Recurrent-Highway-Hypernetworks-NIPS · GitHub
• Using Artificial Intelligence to Augment Human Intelligence
• Learning from Imbalanced Classes - Silicon Valley Data Science
• Regular Expressions for Data Scientists
• Google Developers Blog: Introducing TensorFlow Feature Columns
• bharathgs/Awesome-pytorch-list: A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
• Gaussian Processes – EFavDB
• Neural Smithing
• Hooks Data says…
• Introduction to Various Reinforcement Learning Algorithms. Part I (Q-Learning, SARSA, DQN, DDPG)
• Introduction to Python Ensembles
• Data Science Summit 2018
• facebookresearch/Detectron · GitHub
• GitHub - openai/gradient-checkpointing: Make huge neural nets fit in memory
• Deep-Learning/Skip-Grams-Solution.ipynb at master · priya-dwivedi/Deep-Learning · GitHub
• Recurrent Neural Networks for Drawing Classification  |  TensorFlow
• 2017 news - Gwern.net
• How neural networks are trained
• GitHub - huseinzol05/Emotion-Classification-Comparison: Classification comparison between various models and learning on emotion datasets
• mil-tokyo/webdnn: The Fastest DNN Running Framework on Web Browser
• Beautiful.AI - AI Powered Presentations
• Stanford DAWN Deep Learning Benchmark (DAWNBench) ·
• Introduction to Learning to Trade with Reinforcement Learning – WildML
• Play with Kubernetes
• Deep Reinforcement Learning Doesn't Work Yet
• Release 0.5.0 · PAIR-code/deeplearnjs · GitHub
• Teaching RL
• Introducing the Uber AI Residency
• The Matrix Calculus You Need For Deep Learning

Contributing

Have anything in mind that you think is awesome and would fit in this list? Feel free to send a pull request.

License

To the extent possible under law, Rahul Kumar has waived all copyright and related or neighboring rights to this work.