Manning.Grokking.Deep.Reinforcement.Learning.无水印版pdf

英文图书，文字版，非扫描版。有趣又能学到东西，很好的一本书，自己介绍不好，以下是搞自某读书的书评： 1. 适合算法入门，简单浅显，作者描述的很清楚，是入门算法很合适的书，简单的英文的也可以锻炼自己的外文水平。 2. 私以为此书非常好的完成了他的任务：算法简介。书中去掉了繁琐的公式推导，着重于概念讲解，真正的浅了下来。想要对算法有所深入，还是必须要啃大部头的，但作为入门和复习来说，此书非常合适。 3. 为作者把枯燥抽象的理论讲解得形象生动有趣而点个赞！ 4. 哦天呐 瞧瞧这本算法书写的 我要是一开始看算法是看这本 我一定会更喜欢研究算法的_(:з」∠)_ 这是我看过最精彩的算法入门书了 5. 不是一本高大全的算法和数据结构书，通篇只简单讲解了分治、递归、BFS、Dijkstra、动态规划、贪婪算法等。但是配图有趣易懂，使用python代码，比伪代码更易懂，比Java或C更容易写。我认为非常适合作为算法和数据结构的入门读物，读完会对算法和数据结构有不错的了解，并且皆有可能勾起深入学些了解的兴趣。

北美算法题。用于应对面试的算法题。

, you will not only learn deep reinforcement learning but also become an active contributor to the field. Deep reinforcement learning has the potential to revolutionize the world as we know it. By removing humans from decision-making processes, we set ourselves up to succeed. Humans can't match the stamina and work ethic of a computer;

Grokking+System+Design.pdf

Grokking-the-System-Design-Interview.pdf

Grokking the System Design Interview. For self-study only.

MEAP Edition Manning Early Access Program Grokking Deep Learning Version 10

Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them. Table of Contents Chapter 1. Introduction to algorithms Chapter 2. Selection sort Chapter 3. Recursion Chapter 4. Quicksort Chapter 5. Hash tables Chapter 6. Breadth-first search Chapter 7. Dijkstra’s algorithm Chapter 8. Greedy algorithms Chapter 9. Dynamic programming Chapter 10. K-nearest neighbors

Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you’ll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you’re done, you’ll be fully prepared to move on to mastering deep learning frameworks