神码ai人工智能写作机器人_机器学习和人工智能最佳书籍

神码ai人工智能写作机器人

Here you will get list of best books for Machine Learning and Artificial Intelligence that are useful for beginners and intermediates.

在这里，您将获得有关机器学习和人工智能的最佳书籍清单，这些书籍对初学者和中级者很有用。

Hope you all are doing good. We are again here in front you all with another successive post on Machine Learning. We almost have covered the theoretical portion of the course and will be doing the hands-on practical soon. We all know that there are plenty of resources on the internet that we can use to study and learn almost anything. But again availability of the contents in such a humongous amount haunts the learners that where to start their journey and very often a learner ends up confused and irritated. Great scholars suggest reading books, ain’t they? So why don’t we take the easier path? While the internet is full of plenty of choices that seem very confusing for a novice, we would suggest to start the journey with conventional steps, of course books.

希望大家都做的很好。 我们再次在此面前着另一篇有关机器学习的文章。 我们几乎涵盖了该课程的理论部分，并将很快进行动手实践。 我们都知道，互联网上有很多资源可用于学习和学习几乎所有东西。 但是，如此大量的内容又一次困扰着学习者，使他们从何处开始旅程，而且常常使学习者感到困惑和烦恼。 伟大的学者建议读书，不是吗？ 那么，为什么我们不走更简单的道路呢？ 尽管互联网上有很多选择，对于新手来说似乎很令人困惑，但我们建议您从传统步骤开始学习，当然也要包括书本。

Again you guys do not really worry or need to wander here and there in search of books neither you have to ask someone else’s suggestion for what book to have. Here we have complied a list of some useful books that will give a kick-start to your effort towards data sciences and analytics also on the other hand are interesting to read. Moreover keeping in mind our readers convenience, we’ve also provided the links from where you can order books of your choice without even stepping out of the comfort of your home.  So without talking much let’s get started and step toward the list we have compiled for you.

你们再一次不必担心或到处乱逛寻找书籍，也不必问别人对买什么书的建议。 在这里，我们整理了一些有用的书的清单，这些书将为您在数据科学和分析方面的工作提供一个开端，另一方面，它们也很有趣。 此外，为了方便读者阅读，我们还提供了一些链接，您可以在其中订购所需的书籍，而不必离开家中的舒适环境。 因此，不用多说，让我们开始吧，迈向我们为您编制的清单。

最佳机器学习书籍(ML) (Best Books for Machine Learning (ML))

统计学习的要素 (The Elements of Statistical Learning)

As the name itself suggests, this book aims at explaining the algorithms of machine learning mathematically with a tint of statistics. The three authors are Trevor Hastie, Robert Tibshirani and Jerome Friedman has emphasized on explaining the logic behind the machine learning algorithms with the help of mathematical derivations.

顾名思义，这本书的目的是在数学上用统计色彩解释机器学习的算法。 这三位作者是Trevor Hastie，Robert Tibshirani和Jerome Friedman强调了借助数学推导来解释机器学习算法背后的逻辑。

Note: If you have a good grasp of linear algebra, we would suggest to go with this book.

注意 ：如果您对线性代数有很好的了解，我们建议您阅读本书。

Python机器学习实例 (Python Machine Learning by Example)

Instead you can buy this book written by Yuxi (Hayden) Liu. With this book you will be able to learn the fundamentals of machine learning and would be able to build your own intelligent applications.

相反，您可以购买由Yuxi(Hayden)Liu撰写的这本书。 通过这本书，您将能够学习机器学习的基础知识，并能够构建自己的智能应用程序。

Note: Please note there is no pre-requisite to start with this book. Even a person with zero knowledge about machine learning can easily get a grasp over the course.

注意 ：请注意，本书没有先决条件。 即使是一个对机器学习的知识为零的人也可以很容易地掌握整个课程。

从数据中学习 (Learning from Data)

This very books provide a simplified understanding of the complex areas of machine learning. Instead of lengthy explanations, small and to-the point explanation is being provided by Yaser Abu Mostafa, Malik Magdon Ismail and Hsuan-Tien Lin. We would suggest this book as a good means to learn and apply the principles of machine learning for the beginners.

这些书对机器学习的复杂领域提供了简化的理解。 Yaser Abu Mostafa，Malik Magdon Ismail和Hsuan-Tien Lin不再提供冗长的解释，而是提供小而精要的解释。 我们建议这本书是初学者学习和应用机器学习原理的好方法。

Moreover in addition to the book reading you can also refer to online tutorials by Yaser Abu Mostafa.

此外，除了阅读书之外，您还可以参考Yaser Abu Mostafa的在线教程 。

编程集体智慧 (Programming Collective Intelligence)

This book popularly known as PCI in the world of machine learning is said to have all that requires to start learning machine learning. It is believed that this book was written long before the evolution of machine learning as we see it today, but to our surprise, the topics and chapters discussed entirely relate to the version of machine learning we have today.

据说这本书在机器学习领域广为人知，具有开始学习机器学习所需的全部知识。 可以相信，这本书是在我们今天看到的机器学习发展之前就写的，但是令人惊讶的是，所讨论的主题和章节完全与我们今天拥有的机器学习版本有关。

We strongly recommend this book to every aspiring data scientist, ml enthusiast and even folks who are into machine learning since quite a few time. We bet you won’t regret giving this book a try.

我们强烈推荐这本书给每位有抱负的数据科学家，ml爱好者以及甚至很多时间以来从事机器学习的人们。 我们打赌您不会后悔尝试这本书。

Tom Mitchell的机器学习 (Machine Learning by Tom Mitchell)

After reading the book mentioned just above, we would recommend you to give this too a try. Tom has tried to make his readers understand the concept of machine learning with the help of pseudocodes and case studies. You will also find some interesting basic examples to understand the algorithms with ease.

阅读完上述书籍后，我们建议您也尝试一下。 汤姆(Tom)试图借助伪代码和案例研究使读者理解机器学习的概念。 您还将找到一些有趣的基本示例，以轻松理解算法。

人工智能最佳书籍(AI) (Best Books for Artificial Intelligence (AI))

人工智能：一种现代方法 (Artificial Intelligence: A Modern Approach)

This book is considered as the holy book for understanding the immense field of AI. Peter Norvig and Stuart Russell worked together to make this art happen. This book is suited to the people new to AI. Not only this provides an overview about AI but also covers some advanced topics like search algorithms, working with logic, machine learning, language processing, etc.

这本书被视为了解AI广阔领域的圣书。 彼得·诺维格 ( Peter Norvig)和斯图尔特·罗素 ( Stuart Russell )共同努力，使这种艺术得以实现。 这本书适合AI新手。 这不仅概述了AI，还涵盖了一些高级主题，例如搜索算法，逻辑处理，机器学习，语言处理等。

人工智能编程范式 (Paradigm of Artificial Intelligence Programming)

This book too is written by Peter Norvig. This book primarily aims at teaching its readers the common lisp techniques to build robust AI systems. Instead of just teaching theory, in this book Norvig has put more emphasis on the practical part to let his readers develop programs and systems at their own. If a personnel want to make his/her career in the AI domain, this book is worth giving a shot.

这本书也是彼得·诺维格 ( Peter Norvig )写的。 本书的主要目的是教给读者常见的Lisp技术以构建强大的AI系统。 在本书中，Norvig不仅仅是教授理论，还更加注重实践部分，以使读者可以自己开发程序和系统。 如果人员想在AI领域从事自己的职业，那本书值得一试。

人类人工智能 (Artificial Intelligence for Humans)

Jeff Heaton, the author of this book aims to teach his readers the basic AI algorithms like clustering, error calculation, linear regression, etc. This book is well equipped with good examples and relevant test cases. Moreover this book demands good grasp on mathematics in order to understand the equations described.

本书的作者杰夫·希顿 ( Jeff Heaton)旨在教给读者一些基本的AI算法，例如聚类，误差计算，线性回归等。本书配备了很好的示例和相关测试案例。 此外，本书要求对数学有很好的掌握，以便理解所描述的方程式。

人工智能第一门课程 (A First Course in Artificial Intelligence)

This book is an introductory step towards AI and written by Deepak Khemani. This book is written in such a manner that a person from non-programming background can also understand the concepts easily. Although the advanced topics are not explained into depth, but the overall structure of the book is acceptable. The books explains the classical methods and the updated concepts as well.

本书是Deepak Khemani撰写的迈向AI的入门课程。 本书的编写方式使非编程背景的人也可以轻松理解这些概念。 尽管没有深入解释高级主题，但是本书的总体结构是可以接受的。 这些书解释了经典方法和更新的概念。

Any doubts or suggestions are welcomed in the comment section below. Also let us know if there is any other best books for machine learning and artificial intelligence you have read and is worth mentioning in the list.

如有任何疑问或建议，请访问下面的评论部分。 还请让我们知道您是否已经阅读过其他值得一提的关于机器学习和人工智能的最佳书籍。

翻译自: https://www.thecrazyprogrammer.com/2018/03/best-books-for-machine-learning-and-artificial-intelligence.html

神码ai人工智能写作机器人