For a scientific topic like Machine Learning (or any academic topic from fluid dynamics to literary linguistics), my approach is usually Full-length video courses + TextBooks.
For a practical platform like TensorFlow I tend to start (phase 1) with a couple (2-5) of video tutorials for a high level overview. I then move to (phase 2) written tutorials that show code samples and explain the code. The more samples and the smoother the progression from simple to more complex the better. After a couple (again 2-5) of tutorials I move to (phase 3) trying to implement a few things relying on documentation (official guide/API docs).
Books sometimes can be part of phase 2 as some books are basically written as very good tutorials (like these 3 here 2).