General Books

C++ Books:

The general-purpose programming vernacular C++ books were established to improve the enjoyment of programming for the experienced coder. The book of C++ is a superset of the C programming language, with a few minor exceptions. C++ offers versatile and also effective facilities for defining new types in comparison to the regular offered by C. By creating new types that closely mirror the application’s principles, a programmer can divide an application into digestible chunks. Data abstraction is a term use frequently to describe this method of program design. Some user-defined kinds of objects provide type information. In General Books, we present many books to download for free.

When their type can sometimes be known at compile time, such objects can be utilized conveniently and safely. Programming that makes use of such objects is sometimes referred to as object-based. When properly applied, these strategies produce programs that are shorter, simpler to comprehend, and simpler to execute. Encrypted using an encryption algorithm, guaranteed data activation, dynamic typing, implicit type conversion for user-defined types, user-controlled defragmentation, and also techniques for overloading operators are all provided by classes.

In comparison to C, C++ offers far superior tools for type checking and expressing modularity. Additionally, it includes enhancements that not specifically connect to classes, such as benchmark types, default function arguments, overloaded function names, default function lines of argument offline, free local management technicians, and symbolic constants. The efficiency with which C can interact with the underlying hardware objects retained in C++ (bits, bytes, words, addresses, etc.).

This makes it possible to implement user-defined types with a satisfying level of efficiency. The standard libraries and C++ programming language are portable. The majority of computers that support C can execute the present implementation.

HTML Books:

Hypertext Markup Language is better known as HTML. Actually, it’s merely a text file with codes in it that instruct the browser on how to display the data. You may instruct the browser to center the content on the page or to display a given string of text as a header with bold type, for instance.

Instead of using the.doc,.txt, or .rtf file extensions, we utilize the.html extension to inform the browser that the text file includes HTML.

Whereas an HTML document is simply a text file, any text editor may use it to create one. You can make use of your operating system’s built-in text editors, Microsoft Word, Pages, or both. However, I will suggest a specific HTML book that is free and is titled Programming Coding General Books if you have a Mac.

The benefit of General Books is that you may view every book in real-time. Although we’ll be concentrating on teaching HTML and CSS in this book.

There are several HTML pages that make up a website. As a result, each HTML file contains one web page. The browser opens a unique file called index.html when you enter a website’s home address, such as https://programmingcoding.com or https://programmingcoding.com. In a summary, this HTML file is identical to all others.

However, the fact that it goes by the name index instructs the browser to open this file when a user accesses the website. You should put the index.html file in the home directory on your server. There are occasional exceptions to this rule, but for the time being, it is how you may access a website’s main page.

Python Books:

Python is a powerful and versatile programming language that widely use in a variety of industries, from web development to data science. There are many Python books available that can help you learn Python, whether you are a complete beginner or an experienced programmer. Here are some of the best Python books for different skill levels and interests:

Python Machine Learning” by Sebastian Raschka and Vahid Mirjalili: For those interested in machine learning and data science, this book is an excellent resource. It covers the basics of machine learning and provides examples of how to use Python libraries such as scikit-learn, TensorFlow, and Keras to build machine learning models.

Python for Data Analysis” by Wes McKinney: This book is a practical guide to using Python for data analysis and visualization. It covers the basics of working with data in Python, including using libraries such as pandas, numpy, and matplotlib, and provides examples of how to use these tools to clean, analyze, and visualize data.

In addition to these books, there are many online resources, tutorials, and video courses available to help you learn Python. The best way to learn Python is to find a resource that works for you, and then practice, practice, practice! Remember that learning a new programming language takes time and effort, but the rewards are well worth it.

In conclusion, There are many excellent books available for learning Python, and the best one for you will depend on your skill level and interests. Whether you’re a beginner looking for a comprehensive introduction to the language or an experienced programmer looking to take your skills to the next level, there’s a book out there that can help you. Remember, the key to becoming a proficient Python programmer is to practice and keep learning.

ML & AI Books

Machine learning and artificial intelligence (ML & AI Books) are rapidly growing fields that are changing the way we live, work, and interact with the world. There are many great resources available for those who want to learn more about these subjects, and in recent years, many free books on these topics have become available.

The following is a list of some of the most popular free machine learning and artificial intelligence books:

“Deep Learning” by Yoshua Bengio, Ian Goodfellow, and Aaron Courville: This book introduces deep learning, which is a type of machine learning that has been particularly successful in recent years. The book covers a range of topics, including neural networks, optimization, and convolutional networks.

“Artificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig: This book provides a comprehensive introduction to artificial intelligence, covering a range of topics such as natural language processing, knowledge representation, and machine learning.

“Reinforcement Learning: An Introduction” by Richard S. Sutton and Andrew G. Barto: This book introduces reinforcement learning, a type of machine learning that is particularly suited to tasks that involve decision-making. The book covers topics such as the Markov decision process, value functions, and Q-learning.

This book introduces Bayesian methods and probabilistic programming, which are increasingly important in machine learning and artificial intelligence. These books are all available for free online, either as downloadable PDFs or as online versions. They are an excellent resource for anyone who wants to learn more about machine learning and artificial intelligence and can be used as a self-study resource or as a supplement to formal education or training. With the right motivation and dedication, these free books can help anyone develop the knowledge and skills needed to succeed in these exciting and rapidly growing fields.