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Hi there guys. I am back again with yet another useful post. This one is going to be about free Python books. Most new Python programmers don’t realise that there are great Python books out there for free and due to their lack of knowledge they pay for expensive ones. Most of these books have the same high quality material which you would expect from a paid book. So without wasting any time let me list them here.

Book list:

• A Beginner’s Python Book
• A Bit of Python and Other Things
• A Guide to Python’s Magic Methods – Rafe Kettler
• Building Skills in Python
• Building Skills in Object-Oriented Design (Python)
• Byte of Python
• Data Structures and Algorithms in Python
• Dive into Python – Mark Pilgrim
• Dive into Python 3 – Mark Pilgrim
• Google’s Python Class
• Google’s Python Style Guide
• Hacking Secret Cyphers with Python – Al Sweigart
• Hitchiker’s Guide to Python!
• How to Think Like a Computer Scientist: Learning with Python – Allen B. Downey, Jeff Elkner and Chris Meyers
  • How to Think Like a Computer Scientist: Learning with Python, Interactive Edition
• Introduction to Programming Using Python – Cody Jackson
• Introduction to Programming with Python
• Introduction to python – Kracekumar
• Invent Your Own Computer Games With Python – Al Sweigart
• Learn Python The Hard Way
• Lectures on scientific computing with python – J.R. Johansson
• Making Games with Python & Pygame – Al Sweigart
• Modeling Creativity: Case Studies in Python – Tom D. De Smedt
• Natural Language Processing with Python
• Porting to Python 3: An In-Depth Guide
• Problem Solving with Algorithms and Data Structures
• Program Arcade Games With Python And Pygame
• Python Bibliotheca
• Python Cookbook – David Beazley
• Python for Fun
• Python for Informatics: Exploring Information
• Python for you and me
• Python in Hydrology – Sat Kumar Tomer
• Python Koans
• Python Module of the Week
• Python Practice Book
• Python Programming – PDF
• Python Scientific Lecture Notes
• Python Standard Library – Fredrik Lundh
• Snake Wrangling For Kids
• Test-Driven Web Development with Python
• The Art and Craft of Programming
• The Programming Historian – William J. Turkel, Adam Crymble and Alan MacEachern
• Think Python – Allen B. Downey
• Wikibooks: Python Programming
• Text Processing in Python – David Mertz
• Welcome to Problem Solving with Algorithms and Data Structures – Brad Miller and David Ranum
• Web2py: Complete Reference Manual, 6th Edition (pre-release) – HTML
• Web2py: Complete Reference Manual, 6th Edition (pre-release) – PDF

I hope you liked today’s post. Make sure that you follow my blog to get regular updates whenever I publish a post. If you have any questions, comments or suggestions which you don’t want to write below then email them to me on yasoob.khld@gmail.com. There is a huge list available here as well.
Here is a quick poll as well. Please make sure that you answer it.

 

 Best Python Resources

The Python community is amazing at sharing detailed resources and helping beginners learn to program with the language. There are so many resources out there though that it can be difficult to know how to find them.
This page aggregates the best general Python resources with descriptions of what they provide to readers.

New to programming

If you're learning your first programming language these books were written with you in mind. Developers learning Python as a second or later language should skip down to the next section for "experienced developers".

• To get an introduction to Python, Django and Flask at the same time, consider purchasing the Real Python course by Fletcher, Michael and Jeremy.
  
• This short 5 minute video explains why it's better to think of projects you'd like to build and problems you want to solve with programming. Start working on those projects and problems rather than jumping into a specific language that's recommended to you by a friend.
  
• CS for All is an open book by professors at Harvey Mudd College which teaches the fundamentals of computer science using Python. It's an accessible read and perfect for programming beginners.
  
• If you've never programmed before check out the Getting Started page on Learn To Code with Me by Laurence Bradford. She's done an incredible job of breaking down the steps beginners should take when they're uncertain about where to begin.
  
• Learn Python the Hard Way is a free book by Zed Shaw.
  
• The Python projects tag on the Twilio blog is constantly updated with fun tutorials you can build to learn Python, such as the International Space Station Tracker with Flask and Redis-Queue, Choose Your Own Adventures Presentations using Flask and WebSockets and Martianify Photos with OpenCV.
  
• A Byte of Python is a beginner's tutorial for the Python language.
  
• Code Academy has a Python track for people completely new to programming.
  
• Introduction to Programming with Python goes over the basic syntax and control structures in Python. The free book has numerous code examples to go along with each topic.
  
• Google put together a great compilation of materials and subjects you should read and learn from if you want to be a professional programmer. Those resources are useful not only for Python beginners but any developer who wants to have a strong professional career in software.
  
• The O'Reilly book Think Python: How to Think Like a Computer Scientist is available in HTML form for free on the web.
  
• Python Practice Book is a book of Python exercises to help you learn the basic language syntax.
  
• Looking for ideas about what projects to use to learn to code? Check out this list of 5 programming projects for Python beginners.
  
• There's a Udacity course by one of the creators of Reddit that shows how to use Python to build a blog. It's a great introduction to web development concepts through coding.
  
• I wrote a quick blog post on learning Python that non-technical folks trying to learn to program may find useful.
  
• Python for you and me is an approachable book with sections for Python syntax and the major language constructs. The book also contains a short guide at the end to get programmers to write their first Flask web application.
  

Python for specific occupations

Python is powerful for many professions. If you're seeking to use Python in a specific field, one of these guides may be the most appropriate for you.

• Python for Social Scientists contains a textbook, course outline and slides for a college course that taught social scientists to use Python for their profession.
  
• Practical Business Python is a blog that covers topics such as how to automate generating large Excel spreadsheets or perform analysis when your data is locked in Microsoft Office files.
  
• Python for the Humanities is a textbook and course on the basics of Python and text processing. Note if you've never worked with Python before the material ramps up quickly after the first chapter so you will likely want to combine it with some other introduction to Python resources.
  
• Practical Python for Astronomers provides open source workshop materials for teaching students studying astronomy to use Python for data analysis.
  

Experienced developers new to Python

If you can already program in another language, these resources are better for getting up to speed because they are more concise when explaining introductory topics.

• Learn Python in y minutes provides a whirlwind tour of the Python language. The guide is especially useful if you're coming in with previous software development experience and want to quickly grasp how the language is structured.
  
• Developers familiar with other languages often have difficulty adapting to accepted Python code style. Make sure to read the PEP8 code style guidelines as well as The Elements of Python Style to know the Python community standards.
  
• How to Develop Quality Python Code is a good read to begin learning about development environments, application dependencies and project structure.
  
• The Python module of the week chapters are a good way to get up to speed with the standard library. Doug Hellmann is also now updating the list for changes brought about from the upgrade to Python 3 from 2.x.
  
• Kenneth Reitz's The Hitchhiker’s Guide to Python contains a wealth of information both on the Python programming language and the community.
  
• Composing Programs shows how to build compilers with Python 3, which is a good undertaking if you're looking to learn both more about the Python language and how compiles work.
  
• Good to Great Python Reads is a collection of intermediate and advanced Python articles around the web focused on nuances and details of the Python language itself.
  

Videos, screencasts and presentations

Videos from conferences and meetups along with screencasts are listed on the best Python videos page.

Curated Python packages lists

• awesome-python is an incredible list of Python frameworks, libraries and software. I wish I had this page when I was just getting started.
  
• easy-python is like awesome-python although instead of just a Git repository this site is in the Read the Docs format.
  

Podcasts

Take a look at the best Python podcasts page for a curated list of both Python-specific and general software development podcasts.

Newsletters

• Python Weekly is a free weekly roundup of the latest Python articles, videos, projects and upcoming events.
  
• PyCoder's Weekly is another great free weekly email newsletter similar to Python Weekly. The best resources are generally covered in both newsletters but they often cover different articles and projects from around the web.
  
• Import Python is a newer newsletter than Python Weekly and PyCoder's Weekly. So far I've found this newsletter often pulls from different sources than the other two. It's well worth subscribing to all three so you don't miss anything.
  
• The Full Stack Python monthly newsletter is a monthly newsletter that focuses on a single topic each month. For example, one month will aggregate great Flask resources, while another month will provide WSGI server configurations.
  

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Book Description:

Murach's Python Programming pdf

If you want to learn how to program but don’t know where to start, this is the right book and the right language for you. From the first page, our unique self-paced approach will help you build competence and confidence in your programming skills. And Python is the best language ever for learning how to program because of its simplicity and breadth…two features that are hard to find in a single language.
But this isn’t just a book for newbies! Our self-paced approach also works for experienced programmers, helping you learn faster and better than you’ve ever learned a language before. By the time you’re through, you will have mastered all of the Python skills that are needed on the job, including those for object-oriented, database, and GUI programming.
To make all of this possible, section 1 of this book presents an 8-chapter course that will get anyone off to a great start. Section 2 builds on that base by presenting the other essential skills that every Python programmer should have. Section 3 shows you how to develop object-oriented programs, a critical skillset in today’s world. And section 4 shows you how to apply all of the skills that you’ve already learned as you build database and GUI programs for the real world.

Preview Murach's Python Programming Pdf

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Configure, manage, and secure a CentOS 7 Linux server to serve a variety of services provided in a sustainable computer's infrastructure.

Author: Bhaskarjyoti Roy, Mohamed Alibi

ISBN-10: 1785282395

Year: 2016

Pages: 416

Language: English

File size:15.2 MB

File format: PDF

Category: Linux & Unix

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Book Description

Python Deep Learning Cookbook pdf

Key Features

• Practical recipes on training different neural network models and tuning them for optimal performance
• Use Python frameworks like TensorFlow, Caffe, Keras, Theano for Natural Language Processing, Computer Vision, and more
• A hands-on guide covering the common as well as the not so common problems in deep learning using Python

Book Description
Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics.
The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios.
What you will learn

• Implement different neural network models in Python
• Select the best Python framework for deep learning such as PyTorch, Tensorflow, MXNet and Keras
• Apply tips and tricks related to neural networks internals, to boost learning performances
• Consolidate machine learning principles and apply them in the deep learning field
• Reuse and adapt Python code snippets to everyday problems
• Evaluate the cost/benefits and performance implication of each discussed solution

About the Author
Indra den Bakker is an experienced deep learning engineer and mentor. He is the founder of 23insights—part of NVIDIA's Inception program—a machine learning start-up building solutions that transform the world's most important industries. For Udacity, he mentors students pursuing a Nanodegree in deep learning and related fields, and he is also responsible for reviewing student projects. Indra has a background in computational intelligence and worked for several years as a data scientist for IPG Mediabrands and Screen6 before founding 23insights.
Table of Contents

1. Programming Environment, GPU Computing, and Cloud Solutions
2. Feedforward Networks
3. Convolutional Neural Networks (CNN)
4. Recurrent and Recursive Neural Networks
5. Reinforcement Learning
6. Generative Adversarial Networks
7. Computer Vision
8. Natural Language Processing
9. Speech Recognition and Video Analysis
10. Time Series and Structured Data
11. Game Playing Agents and Robotics
12. Hyperparameter Selection and Tuning
13. Networks Internals
14. Pretrained Models

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