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Python is used as a scripting language for web applications, embedded in software products as a scripting language, used in artifical intelligence tasks, and for system administration tasks.
The focus of this article is to select some of the finest Python books which are available to download for free.
To cater for all tastes, we have chosen a wide range of books, encompassing general introductions to Python, books that help you develop games, introduce kids to the world of programming, and build Python programming skills. Think Python is a concise and gentle introduction to software design using the Python programming language. Snake Wrangling for Kids is a printable electronic book, for children 8 years and older, who would like to learn computer programming.
There are 3 different versions of the free book (one for Mac, one for Linux and one for Windows). Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation.
This book is made available under the terms of the Creative Commons Attribution Noncommercial No-Derivative-Works 3.0 US License. Pylons is a lightweight web framework built on standard Python tools that provides a robust environment for writing modern web applications. It also helps developers make use of the software’s built-in support for session management, web services, and Ajax. This book is made available under the terms of the GNU Free Documentation License, Version 1.2 or any later version. This book gives a hands-on introduction to the underlying theory and algorithms of computer vision (images, videos, etc). The Python language compes with many powerful modules for handling images, mathematical computing and data mining. This book is designed to be used as the primary textbook in a college-level first course in computing. SubscribeEnter your email address below to receive updates each time we publish new content. Reading books is the best way to gain exposure over a particular subject and get an in-depth understanding. The book covers all the crucial areas regarding Python language and introduces one towards the much-needed techniques that has a huge scope, including simple string concentration to that of recursive decent parsers writing. The book is a complete guide on processing, cleaning, influencing and gathering of data in Python. The book is an exceptional reference when it comes to gaining the most out of Python language.
Python is one of the famous programming languages used by major organizations and corporations.
Python is probably the programming language of choice (besides R) for data scientists for prototyping, visualization, and running data analyses on data sets. There are many libraries, applications and techniques to analyze data in Python that even experts in the field don’t have it all figured out. Wes Mckinney’s Python For Data Analysis is a tour of Pandas, Numpy, Matplotlib for people looking to crunch data with Python. If you are new to Python, you should look at the appendix section of this book(“it talks about Python basics”). If you want to explore more about Scikit-learn, there are two other books Mastering machine learning with scikit learn and  Learning Scikit-learn you should look into.
This is more than a “book” – it is a course, and a very well thought through, well supported course at that. The book introduces the APIs provided by some of the larger social platforms, and also gives a good intro to data munging and analysis of data.
The Natural Language Toolkit (NLTK) is an excellent Python library for processing text and language. I would like to very strongly recommend this book to Python lovers who would like to explore the world of Natural Language understanding, parsing and processing.
Bayesian methods for hackers gives a decent introduction to bayesian inference  from both computational and mathematical point of view.
I found these 8 books really useful and interesting, but it clearly depends on your area of interest.
MySQL is the fastest growing open-source relational database management system with 100 million downloads till date.
This blog introduces the convergence of complementary technologies – Spark, Mesos, Akka, Cassandra and Kafka (SMACK) stack.
If you have the choice working with Python 2 or Python 3, we recomend to switch to Python 3!


Scheme, Forth, SQL, Node.js, Fortran, Erlang, Pascal, Ada, OCaml (new), Lua (new), Clojure (new), and Audio Programming (new). Python supports multiple programming paradigms, primarily but not limited to object-oriented, imperative and, to a lesser extent, functional programming styles. It is a simple and powerful language, perfectly suited for beginners and professional programmers alike. It covers the very basics of programming, and uses the Python 3 programming language to teach the concepts. Each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end.
It offers accurate, author-tested documentation of all the modules in the Python 2.0 Library, together with over 300 annotated example scripts using the modules.
It is well known for its clean architecture and loosely coupled approach, both of which make web development fast, flexible, and easy. It seeks to explain computer vision in simple terms, without becoming too embroiled in theory.
It takes a fairly traditional approach, emphasizing problem solving, design, and programming as the core skills of computer science.
Rather, Python is used to illustrate fundamental principles of design and programming that apply in any language or computing environment. In this world of technology, it is important to know and understand the different technical aspects in the computer system.
It is basically a book written for gaining a better insight about the programming at a beginner’s level and can be used to derive a strong foundation over the subject matter. The book has chapters that cover extensively on the subject generators and iteration techniques. It is made for the area of data intensive applications and provides an excellent introduction on data analysis issues. The book provides a clear cut understanding about the background of Python and what is happening behind the programming language. It offers foundational concepts of computer science in a form that is clear and easy to understand. It is a perfect source when it comes to areas like official library and language references. It is an introductory level book on Python programming language and provides for a clear cut understanding about the various areas of the language like tools and concepts. It is readable and supports multiple programming facilities, provides an exceptional platform for any type of relevant tasks, and last but not the least, allows a better developmental knowledge when it comes to programming language and tools. But for aspiring data scientists, understanding these libraries may be just a few pages away. McKinney is the principal author on Pandas, so he mostly talks about Pandas, and shows you how to employ them effectively to your data set.
Most importantly, the target audience is not Pythonistas, but rather scientists, educators, statisticians, financial analysts, and the rest of the non-programmers who want to effectively perform data analysis in Python. You have to know that this book is not intended for beginners, you should have a good grasp of Python and machine learning to understand the code and machine learning techniques used in this book. As per my knowledge there is no other book that shows you how to implement statistical concepts in Python. You need to know basics of probability and Python programming to understand the code and probability concepts. This is a great book and a good introduction to the application of Bayes’s Theorem in a number of scenarios.
The clear and easy to follow examples are further enhanced through the accompanying virtual machine of the book, allowing you to escape the headache of installing, configuring, and selecting the right version of all the supporting software and libraries.
If you are serious about becoming a data scientist then the first 3 books are a must to have.
This book gives you the practical overview relating the real life problems and how to solve them in python. This book is perfect for any kind of python lover and beginner who wants an easy and progressing way of learning python. This e-book tries to make readers practice each and every example they show up as they progresses and make use of it. But this is my personal best collection of python e-books which I would recommend one to pick up for learning python and start doing some project. This book starts with the most basic concepts and gradually adds new material at a pace that is comfortable to the reader.
Access richly annotated datasets using a comprehensive range of linguistic data structures, and understand the main algorithms for analyzing the content and structure of written communication.


You will learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python.
In some places, the author has deliberately avoided certain Python features and idioms that are not generally found in other languages. It provides a detailed overview of the language and helps in gaining a practical knowledge over the subject. It is the best book to read when it comes to security concepts and deals with forensics, tool integration for complicated protocols like SMB. These books explain everything from the basics of data analysis to the most advanced Python libraries.
If you’re looking for a book that is going to tell you the types of analyses to do, this is not that book, as author assumes that you already  know what kind of analyses you need to perform on your data. The book is some thing more than a summary of machine learning algorithms, because it also shows you how to choose the right algorithim for a problem at hand. The good thing about this book is that it is available for free online, a special thanks to author Allen Downey.  Even if you are not yet a great programmer, you will find the content accessible and will be able to master it through the examples and exercises, because most of the exercises use short programs to run experiments and help readers develop understanding. The theoretical aspects are well accessible and the Python code is sufficiently clear. The PDF version of  the book is freely available from Green Tea Press.
How Google can rank and filter results? Toby Segaran does a very good job in revealing and teaching these algorithms in this book. You can also check out authors website mining the social web, where he writes some really good articles on social media mining.
Some of the examples in the book are really amazing, especially the chapter on supervised classification. Like other dynamic languages, Python is often used as a scripting language, but is also used in a wide range of non-scripting contexts. Therefore I quite researched on free online ebooks and ended up with these 7 free e-books among which you can select any of them and start coding. If you really want your brain to do some work and start learning python the scientist way then you should go with this one. There are already many good books about Python on the market; this book is intended as an introduction to computing. There are different types of computer programming languages and of all those, a few of them turns out to be really helpful and stays at the top of the list. The book is easy to read and understand and provides exceptional solutions for effectively analyzing the data.
As it provides for a strong foundation on the subject, it is apt to be read by beginners and new python programmers. The book is apt to be used by those programmers who already have a good understanding over the Python language. The book uses scikit learn to implement these machine learning algorithims, you should definitely know scikit-learn to run machine learning algorithms in Python. He explains complex algorithms and mathematical concepts with clear examples and code that is both easy to read and useful.
Make sure that you are good at Python programming and are familiar with libraries such as Numpy, Scipy and Matplotlib to get the most out of this book.  The book is available for free online. Books are always to guide you but its always better to keep a project in mind and start coding.
Python is a famous and most useful computer programming that is interactive and extensible in nature. It also touches upon essential subjects like Structure and Introduction of Computer programs. It explains the core of python language clearly and includes interpretations of various python programmers.
Once you work on real life problem and start coding and looking over the related syntax it builds up your skill and also gives you depth knowledge on the language. Learning Python is important as it is a cross platform computer language that is used by giant corporations to do work in a quick and efficient manner.



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