Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI

I thoroughly enjoyed Raschka’s book. It explored a variety of topics on machine learning and deep learning. Some of it was familiar but more than half of it was new knowledge. It expanded my knowledge on the cutting edge methods. Also I liked that all chapters had exercises. If you’re looking for something like this, I highly recommend checking it out.

Being an avid reader of Raschka's excellent Ahead-of-AI newsletter, I was thrilled to find his physical book on the shelf. It's quite pricey, so I really checked out the content before buying but what a gem! Each little "Question" chapter is short, to the point, eminently readable and really clarifies the underlying concepts clearly. So glad I bought it. If you're navigating the space of ML & AI and wanting to understand the technical details but you don't have a strong computer science background, then this is an ideal resource and must-have! And you don't have to read the chapters in order - most of them can be read on their own.

I am a software developer and was excited to find out more about AI programming. This book clearly assumes a very high level of existing understanding of math and core AI concepts. Literarily the first concept gets into "high-dimensional" data and "low-dimensional" vectors. The title is misleading because for a novice an essential question would be "what are low-dimensional" vectors, what is convolution, etc.