At present, Java occupies number 1 rank as the most used programming language since almost all the projects are developed in Java. Python is already occupying 2nd to 4th position and will be the most demanded language after Java in the near future. Python is used with other programming languages on the Internet as well as for developing standalone applications. Python programmers are paid high salaries in the software development industry. Hence, it is time for beginners as well as existing programmers to focus their attention on Python.
Want to learn the Python language without slogging your way through howto manuals? with Head First Python, you'll quickly grasp Pythons fundamentals, working with the built-in data structures and functions. Then you'll move on to building your very own web app, exploring database management, exception handling, and data wrangling. If you're intrigued by what you can do with context managers, decorators, comprehensions and generators, it's all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time.
Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Python uses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multisensory learning experience is designed for the way your brain really works.
Learning Python, published by OReilly, is a comprehensive book for Computer professionals as well as students. The concepts are explained in a simple language with multiple examples for better comprehension. This fifth edition of Learning Python is compiled by Mark Lutz.
Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text to speech, and optical character recognition.
Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects.
This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy to follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R.
The book is intended for master and Ph.D. students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform statistical data analysis.