Effective Python

作者根據自己多年的前後端開發經驗，站在完全零基礎讀者的角度，詳盡介紹了Pytho數據分析的基礎知識，以及大量的開發技巧，全書圍繞著“數據分析三劍客（NumPy、Pandas、Matplotlib）”進行細緻的介紹。這三款工具的知識點非常多，本書儘量系統細緻地介紹最精華的知識點，以便為讀者構建一個完善的知識體系，並且為後續的工作打下堅實的基礎。 每一章後面的實戰題以及練習題，經過精心設計，可以鍛煉讀者的數據分析實戰能力，對於鞏固基礎以及鍛煉技術是非常有幫助的。

This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make results from the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be ma