Python Bibliography
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- Create a list of top 100 Python Books with no description or definitions. Sort by most common. Put 2 double square brackets around each topic. Do not number the topics. Separate each topics with a comma.
- Create a list of top 100 Python Books with no description or definitions. Sort by most common. Put 2 double square brackets around each topic and put an asterisk and a space before the topic. Each topic is on a separate line. Do not number the topics.
- Pandas Brain Teasers - Exercise Your Mind by Miki Tebeka on September 5, 2022
- Python Brain Teasers - Exercise Your Mind by Miki Tebeka on September 5, 2022
- Learn to Code by Solving Problems - A Python Programming Primer by Daniel Zingaro on September 4, 2022
- The Big Book of Small Python Projects - 81 Easy Practice Programs by Al Sweigart on September 4, 2022
- Object-Oriented Python - Master OOP by Building Games and GUIs by Irv Kalb on September 4, 2022
- Z by Jason Brownlee on September 4, 2022
- Cython - A Guide for Python Programmers by Kurt Smith on September 4, 2022
- CPython Internals - Your Guide to the Python 3 Interpreter by Anthony Shaw on September 4, 2022
- Python for Data Science - A Hands-On Introduction by Yuli Vasiliev on September 3, 2022
- Practical Programming, 3rd Edition by Jennifer Campbell, Jason Montojo and Paul Gries
- Expert Python Programming - Fourth Edition by Michal Jaworski and Tarek Ziade
- Black Hat Python, 2nd Edition by Justin Seitz and Tim Arnold
- Python Cookbook by Alex Martelli and David Ascher
- Django for Beginners - Build websites with Python & Django, by William S. Vincent, 2018
- Python for DevOps - Learn Ruthlessly Effective Automation - Python for DevOps - by Noah Gift, Kennedy Behrman, Alfredo Deza, and Grig Gheorghiu, 2020, 978-1-492-05769-7
- Practices of the Python Pro by Dane Hillard
- Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and best practices, you can take your code and your career to a new level. With Practices of the Python Pro, you’ll learn to design professional-level, clean, easily-maintainable software at scale using the incredibly popular programming language, Python. You’ll find easy-to-grok examples that use pseudocode and Python to introduce software development best practices, along with dozens of instantly-useful techniques that will help you code like a pro
- Building Android Apps in Python Using Kivy with Android Studio by Ahmed Fawzy Mohamed Gad
- Start building Python-based Android applications using Kivy with Android Studio. Through in-depth examples, this book teaches you everything you need to create your first Android application in Python and publish on Google Play. Building Android Apps in Python Using Kivy with Android Studio takes you through the basics of…
- Beginning Anomaly Detection Using Python-Based Deep Learning by Sridhar Alla, Suman Kalyan Adari
- Utilize this easy-to-follow beginner’s guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with…
- Practical Cryptography in Python by Christopher K. Monson, Seth James Nielson
- Develop a greater intuition for the proper use of cryptography. This book teaches the basics of writing cryptographic algorithms in Python, demystifies cryptographic internals, and demonstrates common ways cryptography is used incorrectly. Cryptography is the lifeblood of the digital world’s security infrastructure. From governments around the world to…
- Practical Data Science with Python 3 by Ervin Varga
- Gain insight into essential data science skills in a holistic manner using data engineering and associated scalable computational methods. This book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Along the way, you will be introduced to many popular open-source frameworks,…
- Applied Reinforcement Learning with Python, by Beysolow II Taweh
- Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym. Applied Reinforcement Learning with Python introduces you to the theory behind…
- Data Science with Python and Dask, by Jesse C. Daniel
- Dask is a native parallel analytics tool designed to integrate seamlessly with the libraries you’re already using, including Pandas, NumPy, and Scikit-Learn. With Dask you can crunch and work with huge datasets, using the tools you already have. And Data Science with Python and Dask is your guide to using…
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- By: Moshe Zadka
- Explore and apply best practices for efficient application deployment. This book draws upon author Moshe Zadka’s years of Dev Ops experience and focuses on the parts of Python, and the Python ecosystem, that are relevant for DevOps engineers. You’ll start by writing command-line scripts and automating simple DevOps-style tasks….
Python All-in-One For Dummies By: Alan Simpson, John Shovic Your one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There’s almost no type…
Automate the Boring Stuff with Python Automate the Boring Stuff with Python By: Al Sweigart If you’ve ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you? In Automate the Boring Stuff with Python, you’ll learn how to use Python to write…
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- Eric Matthes
- Second edition of the best selling Python book in the world. A fast-paced, no-nonsense guide to programming in Python. This book teaches beginners the basics of programming in Python with a focus on real projects. This is the second edition of the best selling Python book in the…
Python: Python Variables, Python Data Types, Python Control Structures, Python Loops, Python Functions, Python Modules, Python Packages, Python File Handling, Python Errors and Exceptions, Python Classes and Objects, Python Inheritance, Python Polymorphism, Python Encapsulation, Python Abstraction, Python Lists, Python Dictionaries, Python Tuples, Python Sets, Python String Manipulation, Python Regular Expressions, Python Comprehensions, Python Lambda Functions, Python Map, Filter, and Reduce, Python Decorators, Python Generators, Python Context Managers, Python Concurrency with Threads, Python Asynchronous Programming, Python Multiprocessing, Python Networking, Python Database Interaction, Python Debugging, Python Testing and Unit Testing, Python Virtual Environments, Python Package Management, Python Data Analysis, Python Data Visualization, Python Web Scraping, Python Web Development with Flask/Django, Python API Interaction, Python GUI Programming, Python Game Development, Python Security and Cryptography, Python Blockchain Programming, Python Machine Learning, Python Deep Learning, Python Natural Language Processing, Python Computer Vision, Python Robotics, Python Scientific Computing, Python Data Engineering, Python Cloud Computing, Python DevOps Tools, Python Performance Optimization, Python Design Patterns, Python Type Hints, Python Version Control with Git, Python Documentation, Python Internationalization and Localization, Python Accessibility, Python Configurations and Environments, Python Continuous Integration/Continuous Deployment, Python Algorithm Design, Python Problem Solving, Python Code Readability, Python Software Architecture, Python Refactoring, Python Integration with Other Languages, Python Microservices Architecture, Python Serverless Computing, Python Big Data Analysis, Python Internet of Things (IoT), Python Geospatial Analysis, Python Quantum Computing, Python Bioinformatics, Python Ethical Hacking, Python Artificial Intelligence, Python Augmented Reality and Virtual Reality, Python Blockchain Applications, Python Chatbots, Python Voice Assistants, Python Edge Computing, Python Graph Algorithms, Python Social Network Analysis, Python Time Series Analysis, Python Image Processing, Python Audio Processing, Python Video Processing, Python 3D Programming, Python Parallel Computing, Python Event-Driven Programming, Python Reactive Programming.
Variables, Data Types, Control Structures, Loops, Functions, Modules, Packages, File Handling, Errors and Exceptions, Classes and Objects, Inheritance, Polymorphism, Encapsulation, Abstraction, Lists, Dictionaries, Tuples, Sets, String Manipulation, Regular Expressions, Comprehensions, Lambda Functions, Map, Filter, and Reduce, Decorators, Generators, Context Managers, Concurrency with Threads, Asynchronous Programming, Multiprocessing, Networking, Database Interaction, Debugging, Testing and Unit Testing, Virtual Environments, Package Management, Data Analysis, Data Visualization, Web Scraping, Web Development with Flask/Django, API Interaction, GUI Programming, Game Development, Security and Cryptography, Blockchain Programming, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotics, Scientific Computing, Data Engineering, Cloud Computing, DevOps Tools, Performance Optimization, Design Patterns, Type Hints, Version Control with Git, Documentation, Internationalization and Localization, Accessibility, Configurations and Environments, Continuous Integration/Continuous Deployment, Algorithm Design, Problem Solving, Code Readability, Software Architecture, Refactoring, Integration with Other Languages, Microservices Architecture, Serverless Computing, Big Data Analysis, Internet of Things (IoT), Geospatial Analysis, Quantum Computing, Bioinformatics, Ethical Hacking, Artificial Intelligence, Augmented Reality and Virtual Reality, Blockchain Applications, Chatbots, Voice Assistants, Edge Computing, Graph Algorithms, Social Network Analysis, Time Series Analysis, Image Processing, Audio Processing, Video Processing, 3D Programming, Parallel Computing, Event-Driven Programming, Reactive Programming.
Python Glossary, Python Fundamentals, Python Inventor: Python Language Designer: Guido van Rossum on 20 February 1991; PEPs, Python Scripting, Python Keywords, Python Built-In Data Types, Python Data Structures - Python Algorithms, Python Syntax, Python OOP - Python Design Patterns, Python Module Index, pymotw.com, Python Package Manager (pip-PyPI), Python Virtualization (Conda, Miniconda, Virtualenv, Pipenv, Poetry), Python Interpreter, CPython, Python REPL, Python IDEs (PyCharm, Jupyter Notebook), Python Development Tools, Python Linter, Pythonista-Python User, Python Uses, List of Python Software, Python Popularity, Python Compiler, Python Transpiler, Python DevOps - Python SRE, Python Data Science - Python DataOps, Python Machine Learning, Python Deep Learning, Functional Python, Python Concurrency - Python GIL - Python Async (Asyncio), Python Standard Library, Python Testing (Pytest), Python Libraries (Flask), Python Frameworks (Django), Python History, Python Bibliography, Manning Python Series, Python Official Glossary - Python Glossary, Python Topics, Python Courses, Python Research, Python GitHub, Written in Python, Python Awesome List, Python Versions. (navbar_python - see also navbar_python_libaries, navbar_python_standard_library, navbar_python_virtual_environments, navbar_numpy, navbar_datascience)
Bibliography: Books, De-DRM (Calibre and Anna's Archive Shadow Library), Publishers and Publications, WorldCat.org (ISBN), Amazon (ASIN), Apple Books-Kindle-eBooks. (navbar_bibliography - see also navbar_shadow_library, navbar_propaganda)
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