This question was recently asked in the /r/machinelearning subreddit.
You can find the link here: https://www.reddit.com/r/learnmachinelearning/comments/18yzv...
Generally the first question I ask when someone asks me that question is:
What are you trying to do?
If you are learning machine learning to do research, your answer will be very different than if you are learning machine learning to start a business or create something with the ML tools/applications available today.
General knowledge ML book:
* Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 3rd Edition by Aurélien Géron
General knowledge data applications book:
* Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems 1st Edition by Martin Kleppmann
General knowledge statistical machine learning book:
* The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics) 2nd Edition by Trevor Hastie (Author), Robert Tibshirani (Author), Jerome Friedman (Author)
Tooling wise, the rabbit hole goes very deep depending on what technologies and what areas you are exploring. Anything from PyTorch all the way to programming GPUs and how to store / work with massive data as well as general algos to work with all of this.