Some ot the text books i prefer: 1. Galactic Astronomy and Dynamic (Binney and Merrifield) 2. Stellar Evolution and Structure 3. Statistics Data Mining And Machine Learning (Ivezic) 4. Pattern Recognition (Bishop) etc and many more.

 Statistics, Data Mining and Machine Learning in Astronomy by Zeljko Ivezic

This book is about the ML in astronomy. The author describes the theory and pyhton code very detailly. This book is mainly for the astronomers who want to use ML algorithm in their research.

 The ML book from Christopher M. Bishop for pattern recognition and Machine learning

This book is mostly used for Computer vision, image processing and image classification. One of the famous book of this area.

 An introduction ot modern astronomy from Caroll and ostlie

This book is one of the important book for astronomers. It describes the theory and equations from scratch to advance. I enjoyed learning this book a lot. From galaxy to stellar, it almost cover each and every topic of Astronomy and Astrophysics. The theory and exercise both are exceptionally good for astronomers.

 Galactic astronomy from Janes Binney and Michael Merrifield

This book is one of the important book for galactic astronomers. It describes the theory and equations from scratch to advance for the galaxy. I enjoyed learning this book a lot. It almost cover each and every topic of galactic astronomy

 Galactic dynamics from Janes Binney and Michael Merrifield

This book along with Galactic astronomy are about the complete concept of galaxy.

 Theory of stellar structure and Evolution by Dina Prialnik

The author describes things that are happening in star in very datail. The internal structure structure of the stars, their life cycle and many more. I found the concept is very clearn, but the author skip significant steps in the derivationof the equation. Its part second about stellar atmosphere make it complete book.