Some that i am looking into; these are "practical" books which do not focus on the theory/algorithms but given that they are available (library/models/whatever), how to build your apps using them;
1) Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications by Chip Huyen.
2) AI Engineering: Building Applications with Foundation Models by Chip Huyen (this is a very recent book).
3) Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play by David Foster.
4) Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG by Bouchard & Peters.
1) Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications by Chip Huyen.
2) AI Engineering: Building Applications with Foundation Models by Chip Huyen (this is a very recent book).
3) Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play by David Foster.
4) Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG by Bouchard & Peters.