goodrahstar / my-awesome-AI-bookmarks

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

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

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Contributing

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

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License

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