- Deep Learning Book - Excellent and current book for the emerging area of Deep Learning.
- Doing Data Science - Has chapters with lectures from different industries and how they apply ML. Also, good introductory chapter on how to build an effective Data Science team.
- Machine Learning - The classic text book for the field. A new edition is coming up shortly and drafts can be found at this link.
- Hands-On Machine Learning with Scikit-Learn and Tensorflow - If you're ready to get hands on, this book is an excellent choice. Even covers Reinforcement Learning with Deep Q-networks.
- Reinforcement Learning - If you are ready to delve into Reinforcement Learning, this is the reference text in many (probably most) university classes.
- Deep Learning School (optimizing model): https://youtu.be/F1ka6a13S9I?t=21m52s
- Stanford Winter Quarter 2016 class: CS231n: Convolutional Neural Networks for Visual Recognition: https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC
- Kubernetes: https://kubernetes.io/docs/home/
- TensorFlow: https://www.tensorflow.org/
- Awesome link for key deep learning papers: https://github.com/terryum/awesome-deep-learning-papers
- StarCraft II API
- Contributing to Google Cloud Open Source Projects - a brief presentation I made at FOSSASIA Summit 2017
- How a Japanese cucumber farmer is using deep learning and TensorFlow
- DeepMind AI Reduces Google Data Centre Cooling Bill by 40%
- Large-scale cluster management at Google with Borg
- Borg: The Predecessor to Kubernetes
- Cloud Native Computing Foundation
- TensorFlow: An open-source software library for Machine Intelligence
- Build and train machine learning models on our new Google Cloud TPUs
- Preventing Overfishing with Machine Learning and Big Data Analytics (Google Cloud Next '17)
- Machine Learning Applications for Data Center Optimization