Fundamentals of Python programming

For courses in computer programming. Evaluating the Fundamentals of Computer Programming LanguagesConcepts of Computer Programming Languages introduces students to the fundamental concepts of computer

A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, s

In mechanical engineering the trend towards increasingly flexible solutions is leading to changes in control systems. The growth of mechatronic systems and modular functional units is placing high dem

Learn to code like a professional with Python – an open source, versatile and powerful programming languageAbout This BookLearn the fundamentals of programming with Python – one of the best languages

Making Things Smart teaches the fundamentals of the powerful ARM microcontroller by walkingbeginners and experienced users alike through easily assembled projects comprised of inexpensive, hardware-st

Gain the fundamentals of x86 64-bit assembly language programming and focus onthe updated aspects of the x86 instruction set that are most relevant to applicationsoftware development. This book covers

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer

The programming landscape of natural language processing has changed dramatically in the past few years. Machine learning approaches now require mature tools like Python’s scikit-learn to apply

Learning Python just got fun for kids!Learning to code is just like playing a new sport or practicing an instrument—just get started! From the basic building blocks of programming to creating your ver

Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python. What You Will LearnUse Python and numerical computation to demonstrate the power of simulationChoose a paradigm to run a simulationDraw statistical insights from numerical experimentsKnow how simulation is used to solve real-world problems Who This Book Is ForEntry-level to mid-level Python developers from various backg

As an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.While there are many books, websites, and online courses about the topic, we break down Python programming into easily digestible lessons of less than 5 minutes each, following our BiteSize approach. Each lesson begins with a clear and short introduction to the topic. This gives you a strong base to start from and gets you ready for deeper learning. Then, you will see coding demonstrations that show the ideas discussed. These examples are simple and useful, helping you really understand the concepts. You'll then practice tasks at different difficulty levels, so you can test your knowledge and increase your confidence. You'll also play with case studies to solve real-world problems. Tips are included to show how you can incorporate generative AI int

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.