Название: Web Coding & Development All-in-One For Dummies, 2nd Edition
Автор: Paul McFedries
Издательство: For Dummies
Год: 2024
Страниц: 851
Язык: английский
Формат: pdf (true), epub
Размер: 36.6 MB

Learn the in-demand skills that let you turn lines of code into websites and apps. Web Coding & Development All-in-One For Dummies is a one-stop resource for would-be developers who need guidance on the languages and steps used to build websites and applications. Learn the coding ropes and expand your existing skillset with this easy-to-understand guide. In these complete mini-books, you’ll walk through the basics of web development, structuring a page, building and processing web forms, and beyond. Learn how to build a website or create your very own app with the advice of web coding and development experts. This edition expands jаvascript and CSS coverage while providing new content on server-side coding and the development stack. In this book, I give you a complete education on web coding and development. You learn how to set up the tools you need, how to use HTML and CSS to design and build your site, how to use jаvascript to program your pages, and how to use PHP and MySQL to program your web server. I show you that these technologies aren’t hard to learn, and that even the greenest rookie programmers can learn how to put together web pages that will amaze their family and friends (and themselves). This Dummies All-in-One is great for you if want to develop coding skills but don’t have a programming background. It’s also perfect for professionals looking to brush up on their web development skills and get up to date on the latest trends and standards.

Название: Statistics Slam Dunk: Statistical analysis with R on real NBA data (Final Release)
Автор: Gary Sutton
Издательство: Manning Publications
Год: 2024
Страниц: 672
Язык: английский
Формат: pdf (true)
Размер: 16.8 MB

Learn statistics by analyzing professional basketball data! In this action-packed book, you’ll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. Statistics Slam Dunk upgrades your R data science skills by taking on practical analysis challenges based on NBA game and player data. Is losing games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Each chapter in this one-of-a-kind guide uses new data science techniques to reveal interesting insights like these. And just like in the real world, you’ll get no clean pre-packaged datasets in Statistics Slam Dunk. You’ll take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team. Amazing insights are hiding in raw data, and statistical analysis with R can help reveal them! R was built for data, and it supports modeling and statistical techniques including regression and classification models, time series forecasts, and clustering algorithms. And when you want to see your results, R’s visualizations are stunning, with best-in-class plots and charts. Statistics Slam Dunk: Statistical analysis with R on real NBA data is an interesting and engaging how-to guide for statistical analysis using R. It’s packed with practical statistical techniques, each demonstrated using real-world data taken from NBA games. In each chapter, you’ll discover a new (and sometimes surprising!) insight into basketball, with careful step-by-step instructions on how to generate those revelations.

Название: Machine Learning Theory and Applications: Hands-on Use Cases with Python on Classical and Quantum Machines
Автор: Xavier Vasques
Издательство: Wiley
Год: 2024
Страниц: 510
Язык: английский
Формат: pdf (true)
Размер: 38.9 MB

Enables readers to understand mathematical concepts behind data engineering and machine learning algorithms and apply them using open-source Python libraries. Machine Learning Theory and Applications delves into the realm of machine learning and deep learning, exploring their practical applications by comprehending mathematical concepts and implementing them in real-world scenarios using Python and renowned open-source libraries. This comprehensive guide covers a wide range of topics, including data preparation, feature engineering techniques, commonly utilized machine learning algorithms like support vector machines and neural networks, as well as generative AI and foundation models. To facilitate the creation of machine learning pipelines, a dedicated open-source framework named hephAIstos has been developed exclusively for this book. Moreover, the text explores the fascinating domain of quantum machine learning and offers insights on executing machine learning applications across diverse hardware technologies such as CPUs, GPUs, and QPUs. Finally, the book explains how to deploy trained models through containerized applications using Kubernetes and OpenShift, as well as their integration through machine learning operations (MLOps). Machine Learning Theory and Applications is an essential resource for data scientists, engineers, and IT specialists and architects, as well as students in computer science, mathematics, and bioinformatics. The reader is expected to understand basic Python programming and libraries such as NumPy or Pandas and basic mathematical concepts, especially linear algebra.

Название: Многозадачность в Python. Многопоточное программирование
Автор: Шибаев Александр
Издательство: Stepik
Год: 2023
Формат: DOCX
Страниц: много
Размер: 3.8 Mb
Язык: Русский

Все о многопоточном программировании на Python в теории и на практике от А до Я. Создание потоков, работа с пулом потоков, курс полностью раскрывает тему поточной многозадачности.

Название: Bash Scripting for Cybersecurity: Mastering Bash for Next-Generation Security Operations
Автор: Jeffery Owens
Издательство: Independently published
Год: 2024
Страниц: 101
Язык: английский
Формат: pdf
Размер: 16.4 MB

Are you ready to supercharge your cybersecurity skills and become a scripting master?Introducing "Bash Scripting for Cybersecurity." This comprehensive guide is your key to unlocking the full potential of Bash scripting in the world of modern cybersecurity. In this book, you'll explore the power of Bash scripting, a must-have skill for security professionals. Learn how to automate security tasks, enhance your analysis, and strengthen your defenses with Bash. Covering everything from Bash essentials and scripting fundamentals to real-time monitoring, incident response automation, and DevSecOps integration. This book aims to take you from a novice to an experienced scripter and equip you with the knowledge and techniques to excel in the ever-evolving field of cybersecurity. Don't miss out on this opportunity to elevate your cybersecurity game. Grab your copy of "Bash Scripting for Cybersecurity" and join the ranks of scripting experts!

Название: Learn Concurrent Programming with Go (Final)
Автор: James Cutajar
Издательство: Manning Publications
Год: 2024
Страниц: 392
Язык: английский
Формат: epub
Размер: 16.6 MB

Write concurrent code in Go that improves application performance, scales up to handle bigger loads, and takes full advantage of modern multi-processor hardware. Learn Concurrent Programming with Go teaches you how to use concurrency to improve the performance of your Go applications. Each chapter poses a new problem that can be solved using concurrency and introduces the right approach to implement it in Go. In this easy-to-read tutorial, you’ll delve into concurrency patterns, learn to dodge the most common pitfalls, and take advantage of Go’s innovative approach to concurrency. Practical exercises at the end of each chapter help you practice your new skills to lock in what you’ve learned. Concurrent programming is essential for getting the most out of modern multi-processor computer hardware. It allows multiple tasks to execute and interact simultaneously, speeding up performance and reducing user wait time. Thanks to its baked-in concurrency models, Google’s Go is one of the best languages you can use to learn and apply concurrent programming to your systems. This book is for readers who already have some programming experience and would like to learn about concurrency. The book assumes no prior knowledge of concurrent programming. Though the ideal reader would already have some experience with Go or another C-syntax-like language, this book is also well suited for developers coming from any language—if some effort is spent learning Go’s syntax.

Название: Ultimate Splunk for Cybersecurity: Practical Strategies for SIEM Using Splunk's Enterprise Security (ES) for Threat Detection, Forensic Investigation, and Cloud Security
Автор: Jit Sinha
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 463
Язык: английский
Формат: pdf, epub (true)
Размер: 10.1 MB

Empower Your Digital Shield with Splunk Expertise! The Ultimate Splunk for Cybersecurity is your practical companion to utilizing Splunk for threat detection and security operations. This in-depth guide begins with an introduction to Splunk and its role in cybersecurity, followed by a detailed discussion on configuring inputs and data sources, understanding Splunk architecture, and using Splunk Enterprise Security (ES). It further explores topics such as data ingestion and normalization, understanding SIEM, and threat detection and response. It then delves into advanced analytics for threat detection, integration with other security tools, and automation and orchestration with Splunk. Additionally, it covers cloud security with Splunk, DevOps, and security operations. Moreover, the book provides practical guidance on best practices for Splunk in cybersecurity, compliance, and regulatory requirements. It concludes with a summary of the key concepts covered throughout the book. Machine-generated data refers to any digital information generated by devices, applications, or systems. This includes log files, sensor data, application performance monitoring (APM) data, and many more. Since organizations continue to rely heavily on digital systems, the volume of machine-generated data increases exponentially. Traditional data management and analysis tools often struggle to keep up with this data growth, leading to a need for specialized solutions like Splunk.

Название: Handbook of Research on Artificial Intelligence and Soft Computing Techniques in Personalized Healthcare Services
Автор: Uma N. Dulhare, A.V. Senthil Kumar, Amit Datta
Издательство: Apple Academic Press, CRC Press
Серия: AAP Advances in Artificial Intelligence and Robotics
Год: 2024
Страниц: 493
Язык: английский
Формат: pdf (true)
Размер: 35.2 MB

This volume demonstrates the diverse state-of-the-art applications that combine Artificial Intelligence with soft computing, which has great potential for creating smart personalized healthcare services. The book showcases the myriad uses of AI and computer techniques in healthcare that employ Deep Learning, robotics, Machine Learning, blockchain, emerging cloud, edge computing, Practical Byzantine Fault Tolerance consensus, CNN architecture, Splunk, genetic algorithms (GA), DurBhashan, and many more. These technologies can be used in healthcare for enhanced data sharing, remote health monitoring, tele-rehabilitation, connecting rural populations with healthcare services, identifying diseases and health issues, automated medical diagnosis, analyzing information in surgical videos, ensuring timely communication and transportation during health disasters and emergencies, for optimizing expenditures, and more.

Название: Portfolio Optimization with Python: Code your way to Portfolio Optimization
Автор: Hayden Van Der Post, Alice Schwartz
Издательство: Reactive Publishing
Год: 2023
Страниц: 304
Язык: английский
Формат: pdf
Размер: 43.3 MB

Maximize Your Investment Strategy with Advanced Portfolio Techniques in Python! Unlock the secrets of successful investors and elevate your financial acumen with "Portfolio Optimization with Python: The Sharpe Mindset." Tailored for both seasoned traders and aspiring investment analysts, this comprehensive guide navigates the intricate world of portfolio optimization through the powerful lens of Python programming. Delve into the step-by-step journey from novice to expert as you harness Python's robust libraries and frameworks to analyze financial data, build risk-aware portfolios, and ultimately attain higher returns. With detailed coding examples, this book demystifies complex financial theories and transforms them into practical, actionable strategies. With engaging real-world examples, this book brings theory to life, teaching you not just how to write code, but also how to think like a proficient financial analyst. Whether you're a budding programmer eager to apply your skills to the stock market, or a finance professional aiming to upgrade your toolkit, "Portfolio Optimization with Python: The Sharpe Mindset" is your definitive resource for achieving peak portfolio performance. Are you ready to sharpen your investment edge? Open the pages and start your transformative journey to financial mastery with Python!

Название: Building Neural Networks from Scratch with Python
Автор: L.D. Knowings
Издательство: Independently published
Год: 2023
Страниц: 163
Язык: английский
Формат: pdf
Размер: 33.3 MB

Ready to throw your hat into the AI and Machine Learning ring? Get started right here, right now! Are you sick of these Machine Learning guides that don’t really teach you anything? Do you already know Python, but you’re looking to expand your horizons and skills with the language? Do you want to dive into the amazing world of neural networks, but it just seems like it’s… not for you? Artificial Intelligence is progressing at a fantastic rate—every day, a new innovation hits the net, providing more and more opportunities for the advancement of society. In your everyday life, your job, and even in your passion projects, learning how to code a neural network can be game-changing. But it just seems… complicated. How do you learn everything that goes into such a complex topic without wanting to tear your own hair out? Well, it just got easier. Machine Learning and neural networking don’t have to be complicated—with the right resources, you can successfully code your very own neural network from scratch, minimal experience needed! In this all-encompassing guide to coding neural networks in Python, you’ll uncover everything you need to go from zero to hero—transforming how you code and the scope of your knowledge right before your eyes. By the end of this book, you’ll have mastered neural networks confidently!