Python

Learn even more about coding, and take your computer games to the next level!In 10 easy lessons, learn about adding detailed graphics and take your game designing skills to the next level. Now that yo

Impractical Python is a collection of fun and educational projects designed to entertain programmers while enhancing their Python skills. It picks up where the complete beginner books leave off, expan

The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old,

Python is today's fastest growing programming language. This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader's hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files. This book is perfect for anyone who wants to learn how to program with Python. In particular, students starting out in computer science and teachers who want to improve their confidence in Python will find here a set of ready-made challenges for classroom use.

Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it.

Leverage Python for expert-level volatility and variance derivative tradingListed Volatility and Variance Derivatives is a comprehensive treatment of all aspects of these increasingly popular derivati

A fully updated tutorial on the basics of the Python programming language for science studentsPython is a computer programming language that is rapidly gaining popularity throughout the sciences. This

A fully updated tutorial on the basics of the Python programming language for science studentsPython is a computer programming language that is rapidly gaining popularity throughout the sciences. This

Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer mode

Refine your programming techniques and approaches to become a more productive and creative Python programmer. This book explores the concepts and features that will improve not only your code but also

Learn a simpler and more effective way to analyze data and predict outcomes with PythonMachine Learning in Python shows you how to successfully analyze data using only two core machine learning algori

In FUNDAMENTALS OF PYTHON: FROM FIRST PROGRAMS THROUGH DATA STRUCTURES, Washington and Lee University professor Kenneth A. Lambert presents all of the important topics in CS1 and CS2 in one volume. Th

Discover the Django web application framework and get started building Python-based web applications. This book takes you from the basics of Django all the way through to cutting-edge topics such as c

This is the Python version of our book. See the website for links to the C++ and Java version.Have you ever... Wanted to work at an exciting futuristic company? Struggled with an interview problem tha

Learning to program is one of the best investments that you can make for your research and your career. Python for biologists is a complete programming course for beginners that will give you the skil

Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively

If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language one step at a time, beginning with basic programming concepts

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specif

Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, Foundations of Statistics for Data Scientists: With R and Python is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. The book assumes knowledge of basic calculus, so the presentation can focus on 'why it works' as well as 'how to do it.' Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python.The book also introduces modern topics that do not normally appear in mathematical statistics texts but ar