Master_Machine_Learning_Algorithms下载

AI100_小助手 2018-07-18 05:03:13

Jason Brownlee的Master_Machine_Learning_Algorithms，通俗易懂，零基础
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master_machine_learning_algorithms

Preface Machine learning algorithms dominate applied machine learning. Because algorithms are such a big part of machine learning you must spend time to get familiar with them and really understand how they work. I wrote this book to help you start this journey. You can describe machine learning algorithms using statistics, probability and linear algebra. The mathematical descriptions are very precise and often unambiguous. But this is not the only way to describe machine learning algorithms. Writing this book, I set out to describe machine learning algorithms for developers (like myself). As developers, we think in repeatable procedures. The best way to describe a machine learning algorithm for us is: 1. In terms of the representation used by the algorithm (the actual numbers stored in a file). 2. In terms of the abstract repeatable procedures used by the algorithm to learn a model from data and later to make predictions with the model. 3. With clear worked examples showing exactly how real numbers plug into the equations and what numbers to expect as output. This book cuts through the mathematical talk around machine learning algorithms and shows you exactly how they work so that you can implement them yourself in a spreadsheet, in code with your favorite programming language or however you like. Once you possess this intimate knowledge, it will always be with you. You can implement the algorithms again and again. More importantly, you can translate the behavior of an algorithm back to the underlying procedure and really know what is going on and how to get the most from it. This book is your tour of machine learning algorithms and I’m excited and honored to be your tour guide. Let’s dive in.

《数据结构实战完全手册》主讲：丁宋涛数据结构是程序设计的必修知识，它是程序设计的基本功，并且在企业面试、日常工作、研究生入学考试中都占有重要的地位。不同于其他课程，本课程从单链表出发，手把手的全代码实现了栈与队列，树、图（包括数组和链表的两种形式），并对这些经典结构的应用也做了代码级的实现，覆盖了经典数据结构的全部内容. 课程参考教材：周幸妮教授的《数据结构与算法分析新视角》由德古意特（DE GRUYTER. 德国）和科学出版社联合出版对应英文版《Data Structures and Algorithms Analysis – New Perspectives》

Jason Brownlee的Master_Machine_Learning_Algorithms，通俗易懂，零基础

本书作者是网路有名机器学习专家，本书全以python撰写，并且避免使用第三方函式库，完全让读者了解各种机学习演算的实作，在讲求快速的年代，能真正彻底了解演算法的实作，而不是用keras、tensor flow，组一组、拼一拼，实做了一个四不像的ML演算法，让读者从理论到实作(完全实作)，是本不可多得的好书

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