I am new to AI. Is this a good place to start? If not, can you recommend good starting sources to augment this book?
I have Google Cloud Account, AWS. I have dabbled with the skills.
I'll check other answers for the practical uses so I don't go over my one allowable question.
If you're new to AI, I would recommend first starting with a simple models and usecases. Why I'm saying this is, when jumping directly to deep learning, it's quite easy to lose appreciation for the full ML workflow. I.e.
+ Data cleaning
+ Feature engineering
+ Model evaluation
+ Model interpretation
I try to touch on every one of these topics as much as I can. But due to the nature of deep learning, feature engineering is almost non-existent and even data cleaning is not performed (especially in computer vision). And some don't even think anything beyond once they get to a good accuracy! That's quite wrong because we don't know if the model learned good features if we do not interpret the model.
Unfortunately I don't really have a recommendation in my mind, as I haven't come across a book that covers the whole process end to end as well as goes at a reasonable pace. You can try https://www.manning.com/books/machine-learning-in-action. But I cannot personally endorse this as I haven't read this. If possible best way to do would be to do a course (even a small one) at a university. This way you get face-to-face interaction and the benefit of a well developed syllabus.
Good luck on your journey!
PhD | Senior Data Scientist | AI/ML Educator