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"A learner's guide to real-world programming with C# and .NET"--Cover.

Stellman Andrew: Head First C#

Head First C#

A Learner's Guide to Real-World Programming with C# and .Net

Master the inner workings of your x64 Linux system and expand your OS expertise by writing your very own debugger using C++. If debuggers seem like magic to you, there is no better way to demystify them than to write your own. This book will show you exactly how to do it, walking you through the entire process of building a debugger for x64 Linux systems using C++. As go from an empty filesystem folder to a fully fledged debugger capable of setting breakpoints, stepping through code, manipulating variables, and more, you’ll learn how to: <ul><li>Attach to a process</li><li>Read and write to registers</li><li>Set hardware and software breakpoints</li><li>Output disassembly</li><li>Support multithreading and other tasks</li></ul> As you add features to your debugger, you’ll also pick up a wealth of knowledge about operating systems, compilers, software testing, and low-level programming that you can use in your day-to-day development.

Building a Debugger

Tcl/Tk: A Developer's Guide, Fourth Edition is an essential resource for computer professionals, from systems administrators to programmers. It covers new Tcl features, expanded Tcl-OO coverage, web technology using Rivet and SQLite, and AI integration with AWS. The book also delves into Tcl's standard tools, multi-faceted nature, and extensibility, making it ideal for developing GUIs, client/server middleware, and web applications. Readers will quickly learn to code in Tcl and extend its capabilities with the inclusion of numerous code examples and case studies. The updated edition includes over 150 pages on the latest Tcl extensions, proven techniques, and tools for effective programming. Extensive code snippets and online tutorials enhance understanding, while case studies provide practical insights. The book also discusses Tcl's role as the hidden "secret sauce" in commercial applications, highlighting its graphics and control infrastructure. With a vibrant user community and evolving API, Tcl/Tk remains a powerful and versatile programming platform for both beginners and experienced programmers.

A Developer's Guide

Tcl/Tk

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

Since the first edition of “Data Science and Analytics with Python” we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This has led to book becoming a key textbook among practitioners and students.

Data Science and Analytics with Python

Theoretical and Computational Chemistry

Quantum chemistry requires ever higher computational performance, with more and more sophisticated and dedicated Python scripts being required to solve challenging problems. Although resources for basic use of Python are widely (and often freely) available online and in literature, truly cohesive materials for advanced Python programming skills are lacking. Qiming Sun, a developer of the popular Python package PySCF, provides a comprehensive, end-to-end practical resource for researchers and engineers who have basic Python programming experiences chiefly in computational chemistry but want to take their use of the software forwards to the next level, the book provides an insightful exploration of Numpy, Pandas, and other data analysis tools. Readers will learn how to manage their Python computational projects in a professional way, with various tools and protocols for computational chemistry research and general scientific computing tasks exhibited and analysed from a technical perspective. Multiple programming paradigms including object-oriented, functional, meta-programming, dynamic, concurrent, and vector-oriented are illustrated in various technology scenarios allowing readers to properly use them to enhance their program projects. Readers will also learn how to use the presented optimization technologies to speed up their Python applications, even to the level as fast as a native C++ implementation. The applications of these technologies are then demonstrated using quantum chemistry Python applications. Python for Quantum Chemistry: A Full Stack Programming Guide is written primarily for graduate students, researchers and software engineers working primarily in the fields of theoretical chemistry, computational chemistry, condensed matter physics, material modelling, molecular simulations, and quantum computing.

A Full Stack Programming Guide

Python for Quantum Chemistry: Volume 23

To write effective code and applications, software engineers and developers have to be able to frame user/customer needs effectively, capture program requirements and use cases, and then develop suitable software architecture and code to meet the need. Code Chronicles: The Art of Storytelling in Software helps readers write better software by teaching readers how to write stories in the context of software development. The book explains the roots of storytelling, clarifies that storytelling historically has been a very powerful tool used to pass along knowledge, presents where storytelling is already present implicitly in software development, discusses how to make it more effective, and finally present experiences in storytelling from software engineering and other scientific disciplines, to foster a full understanding of its power. The authors comprehensively present the pivotal role of storytelling in writing software, and they explain how to do it in a simple, hands-on approach, also taking advantage of clear case studies written by experts in the field.

The Art of Storytelling in Software

Code Chronicles

This long-awaited second edition folds years of updates into its beginner-friendly lessons on using R for data and statistical analysis. Even with no programming experience, The Book of R, 2nd Edition will teach everything you need to know to use R effectively in statistical analysis and data visualization. Readers will start with the basics, like how to handle data and write simple programs, before learning more advanced topics, like producing statistical models or creating 3D visualizations. More than 30 hands-on exercises (with downloadable solutions) take readers from theory to practice. The second edition has been updated from start to finish, with new content on statistical operations, data plots, date-time objects, and more — including dozens of fresh exercises.

This long-awaited second edition folds years of updates into its beginner-friendly lessons on using R for data and statistical analysis. Even if you have no programming experience and little more than a grounding in basic math, The Book of R, 2nd Edition will teach you everything you need to know to begin using R effectively in statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data, performing statistical tests, and modeling. You’ll also learn how to create impressive data visualizations with R’s graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Over 30 hands-on exercises (with downloadable solutions) take you from theory to practice, as you explore: <ul><li>The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops</li><li>Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R</li><li>How to access R’s thousands of functions, libraries, and data sets</li><li>How to draw valid and useful conclusions from your data</li><li>How to create publication-quality graphics of your results</li></ul> The long-awaited second edition has been revised and updated from start to finish,&nbsp;folding years of updates into its beginner-friendly lessons on R. It also contains new content that expands the book’s coverage of statistical operations, data plots, date-time-objects, and more — including dozens of fresh exercises to strengthen your skills. Combining detailed explanations with real-world examples, The Book of R is your doorway into the wide world of data analysis. Includes one 8-page full-color insert.

A First Course in Programming and Statistics

The Book of R, 2nd Edition

If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place. <ul> <li>Analyze data distributions and visualize patterns using Python libraries</li> <li>Improve predictions and insights with regression models</li> <li>Dive into specialized topics like time series analysis and survival analysis</li> <li>Integrate statistical techniques and tools for validation, inference, and more</li> <li>Communicate findings with effective data visualization</li> <li>Troubleshoot common data analysis challenges</li> <li>Boost reproducibility and collaboration in data analysis projects with interactive notebooks</li> </ul>

Exploratory Data Analysis

Think STATS

In today's data-driven world, the ability to efficiently analyze and interpret information is more crucial than ever, especially in the business sector. "Python for Excel Users: A Beginner's Guide" is tailored for business students and professionals proficient in Microsoft Excel but are ready to embark on their Python journey.

A Beginner's Guide

Python for Excel Users

"This is the second edition of the essential reference and guidebook for SuperCollider, a powerful, flexible, open-source, cross-platform audio programming language"--

A comprehensive update of the essential reference to SuperCollider, with new material on machine learning, musical notation and score making, SC Tweets, alternative editors, parasite languages, non-standard synthesis, and the cross-platform GUI library. SuperCollider is one of the most important domain-specific audio programming languages, with wide-ranging applications across installations, real-time interaction, electroacoustic pieces, generative music, and audiovisuals. Now in a comprehensively updated new edition, The SuperCollider Book remains the essential reference for beginners and advanced users alike, offering students and professionals a user-friendly guide to the language’s design, syntax, and use. Coverage encompasses the basics as well as explorations of advanced and cutting-edge topics including microsound, sonification, spatialization, non-standard synthesis, and machine learning. Second edition highlights: •&nbsp;&nbsp;&nbsp;New chapters on musical notation and score making, machine learning, SC Tweets, alternative editors, parasite languages, non-standard synthesis, SuperCollider on small computers, and the cross-platform GUI library •&nbsp;&nbsp;&nbsp;New tutorial on installing, setting up, and running the SuperCollider IDE •&nbsp;&nbsp;&nbsp;Technical documentation of implementation and information on writing your own unit generators •&nbsp;&nbsp;&nbsp;Diverse artist statements from international musicians •&nbsp;&nbsp;&nbsp;Accompanying code examples and extension libraries

The SuperCollider Book, second edition

Learn to leverage Python for advanced 3D data processing, visualization, and AI-enabled workflows. Define 3D virtual realms, immersive environments, and digital automation to analyze physical objects. With a focus on practicality, this book offers data scientists, engineers, and developers a hands-on approach to working with 3D data. From 3D reconstruction to 3D deep learning techniques, you'll learn how to extract valuable insights from massive datasets, including point clouds, voxels, 3D meshes, images, and more. Author Florent Poux helps you leverage the potential of cutting-edge algorithms and 3D AI models to develop production-ready systems with a focus on automation. You'll learn how to define 3D systems, leverage powerful algorithms, and deploy 3D digital experiences for your industry (geospatial applications, self-driving cars, medical imaging, robotics, manufacturing, computer vision/graphics, and more). This book dives deep into 3D data science with Python: building 3D workflows and wielding Python to implement your solutions. You'll learn: <ul> <li>Core concepts and representations of 3D data (meshes, point clouds, voxels, CAD) </li><li>How to load, manipulate, analyze, and visualize 3D data using powerful Python libraries </li><li>Advanced AI algorithms for 3D pattern recognition (supervised and unsupervised) </li><li>3D reconstruction techniques to generate 3D datasets </li><li>Automated 3D modeling and generative AI workflows </li><li>Practical applications of 3D data science in areas like computer vision/graphics, geospatial intelligence, scientific computing, robotics, and autonomous driving </li><li>How to build end-to-end 3D Python apps through real-world projects </li></ul> Florent Poux is an esteemed authority in the field of 3D data science who teaches and conducts research for top European universities. He's also head professor at the 3D Geodata Academy and innovation director for French Tech 120.

Building Accurate Digital Environments with 3D Point Cloud Workflows

3D Data Science with Python

Advances in Metaheuristics

This book is structured to guide readers through AGA's concepts, practical applications, and future directions.At its core, this book is an invitation to reimagine the boundaries of algorithmic design. It is crafted for researchers, practitioners, and enthusiasts in computer science, operations research, AI, and beyond.

This book is structured to guide readers through AGA's concepts, practical applications, and future directions.At its core, this book is an invitation to reimagine the boundaries of algorithmic design. It is crafted for researchers, practitioners, and enthusiasts in computer science, operations research, AI, and beyond.

Automatic Generation Of Algorithms

Covering the three underlying technologies of Web pages: HTML, CSS, and JavaScript, this book is a one-stop guide to getting started in web development, be it in a class or as a solo-learner.

Covering the three underlying technologies of Web pages: HTML, CSS, and JavaScript, this book is a one-stop guide to getting started in web development, be it in a class or as a solo-learner.

Developing Web Sites with HTML, CSS and JavaScript

Head First C#

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