Название: Before Machine Learning Volume 1 - Linear Algebra for A.I.: The fundamental mathematics for Data Science and Artificial Inteligence
Автор: Jorge Brasil
Издательство: Independently published
Год: 2023
Страниц: 151
Язык: английский
Формат: pdf, epub + code
Размер: 10.8 MB

Has the abstract nature of linear algebra ever left you overwhelmed? Do you yearn to unlock the essence of machine learning but are bogged down by the intricacy of the mathematics? Dive into a realm where linear algebra unfolds not just as numerical operations, but as a powerful story. A story intertwined with the magic of Machine Learning, making sense of data, and unraveling algorithms that power tomorrow. I am Jorge, a mathematician with over a decade of hands-on experience in Data Science and Machine Learning. Having navigated the intricate pathways of mathematical computations and Machine Learning algorithms myself, I wrote this book that differs itself from a traditional text book. With a conversational style and humour, I will guide through what you've been seeking on your journey into the depths of linear algebra. This book isn’t just about understanding linear algebra—it’s about experiencing it. Dive into real-world applications, and grasp concepts that are foundational to Machine Learning.

Название: Full-Stack jаvascript Strategies: The Hidden Parts Every Mid-Level Developer Needs to Know (Fourth Early Release)
Автор: Milecia McGregor
Издательство: O’Reilly Media, Inc.
Год: 2024-05-16
Страниц: 163
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

As a working software developer, you know how to complete your tasks with solid code, whether it's on the frontend or backend. Now you're ready to move to the next level in your career, and you need to understand the subtle yet deep skills it takes to become a senior developer. This practical book shows you everything it takes to create a full-stack web application hosted on a cloud platform. Senior staff engineer Milecia McGregor helps you see how the whole system works and how senior developers arrive at technical decisions. You'll learn about design and development principles and when to apply them. You'll also discover strategies for working with different teams and understand how the product team makes its decisions. If you are trying to figure out how senior devs seem to magically know how everything works and how they understand complex concepts so quickly, I’m going to show you how. At this point in your career, you’ve probably been working as a software developer for a few years. You know how to complete your tasks with solid code regardless of whether it’s on the front-end or back-end. While you might have some knowledge across the full-stack, it’s likely you have a focus on one part of the stack over the other. On the front-end, you should be familiar with things like making responsive layouts, fetching data from APIs, and some of the frameworks like React, Astro, or Svelte. On the back-end, you’ve done some database migrations, built some APIs, and handled some basic authentication flows.

Название: Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing: Vol 17
Автор: Roger Lee
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2024
Страниц: 177
Язык: английский
Формат: pdf (true), epub
Размер: 35.4 MB

This book reports state-of-the-art results in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. This edited book presents original papers on both theory and practice. It addresses foundations, state-of-the-art problems and solutions, and crucial challenges. Software error detection is a critical aspect of software development. However, due to the lack of time, budget, and workforce, testing applications can be challenging, and in some cases, bug reports may not make it to the final stage. Additionally, a lack of product domain knowledge can lead to misinterpretation of calculations, resulting in errors. To address these challenges, early bug prediction is necessary to develop error-free and efficient applications. In this study, the author proposed a system that uses Machine Learning to analyze system error logs and detect errors in real time. The proposed system leverages imbalanced data sets from live servers running applications developed using PHP and Codeigniter. The system uses classification algorithms to identify errors and suggests steps to overcome them, thus improving the software’s quality, reliability, and efficiency. Our approach addresses the challenges associated with large and complex software where it can be difficult to identify bugs in the early stages. By analyzing system logs, we demonstrate how Machine Learning classification algorithms can be used to detect errors and improve system performance. Our work contributes to a better understanding of how Machine Learning can be used in real-world applications and highlights the practical benefits of early bug prediction in software development.

Название: Performance with Laravel
Автор: Martin Joo
Издательство: Independently published
Год: 2024
Страниц: 362
Язык: английский
Формат: pdf + Sources
Размер: 30.3 MB

With this guide, you can significantly improve the performance of your Laravel/PHP applications. "Performance with Laravel" is a 362-page guide that teaches you how to optimize your app's performance. Advanced Redis, Advanced database indexing, Designing performant and reliable architectures, CQRS, Async workflows, Optimizing jobs and workers, Concurrent programming, Working with large datasets, Export and imports, Decreasing memory consumption, fpm processes, nginx cache, Database optimization techniques, Measuring performance, Fixing N+1 queries, HTTP-related optimizations. All of the above by building real-world projects such as a web scraper or a complete web page analytics platform.

Название: Designing Software Architectures: A Practical Approach, 2nd Edition (Final)
Автор: Humberto Cervantes, Rick Kazman
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2024
Страниц: 455
Язык: английский
Формат: pdf (true)
Размер: 39.7 MB

Learn how to create successful architectural designs and improve your current design practices! Designing Software Architectures, 2nd Edition, provides a practical, step-by-step methodology for architecture design that any professional software engineer can use, with structured methods supported by reusable chunks of design knowledge and rich case studies that demonstrate how to use the methods. The Attribute-Driven Design method may not have changed since this book's first printing, but almost everything else about the industry has. In this newly updated edition, you will find new chapters on supporting business agility through API-centric design, deployability, cloud-based solutions, and technical debt in design. Humberto Cervantes and Rick Kazman illuminate best practices for how architects should design complex systems so you can make design decisions in systematic, repeatable, and cost-effective ways. This book will help you become a better, more confident designer who can create high-quality architectures with ease.

Название: Python in Power BI: Unleash the Power of Python for Dynamic Data Analysis: A Comprehensive Guide to Data Visualization
Автор: Hayden Van Der Post
Издательство: Reactive Publishing
Год: 2024
Страниц: 583
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Unlock the full potential of Power BI by integrating Python! Transform your data analytics capabilities with this comprehensive guide that marries the versatility of Python with the robust features of Power BI. Whether you're a seasoned data analyst or a beginner, 'Python in Power BI' is your ultimate resource for creating dynamic, insightful, and visually compelling data stories. Overview: In today's data-driven world, professionals need tools that offer flexibility, efficiency, and power. 'Python in Power BI' bridges the gap between two of the most powerful tools in data analytics, providing readers with a seamless way to enhance their data visualization and analysis. The origins of Power BI trace back to a desire to make data-driven decision-making more accessible and efficient. Prior to its advent, organizations often relied on disparate tools and systems, leading to fragmented insights and delayed decision-making processes. Power BI addresses these challenges by offering a unified platform where data from various sources can be integrated, analyzed, and visualized seamlessly.

Название: Thinking in Distributed Systems
Автор: Dominik Tornow
Издательство: Independently published
Год: 2024
Страниц: 291
Язык: английский
Формат: pdf, epub
Размер: 41.7 MB

Every modern software system is a distributed system. Whether you are building a web app, mobile app, or cloud service, understanding the fundamental principles and practices of distributed systems is essential for any software engineer. However, I struggled to find comprehensive resources while mastering distributed systems. That's why I wrote this book – to share my knowledge and experience I gained over 15 years of studying and working with distributed systems. This book is a comprehensive overview of the key concepts in distributed systems, consisting of 12 concise yet easy-to-follow chapters. What You Get From This Book: - Advance your career; - Pursue senior and leadership roles with a deep understanding of distributed systems; - Go from beginner to expert; - Bridge the gap from beginner and expert, master the skills needed to succeed in distributed systems; - Think like the experts; - Learn how to approach complex problems with the mindset and the confidence of an expert; - Learn the theoretical foundations; - Tackle complex challenges and contribute valuable insights with a strong foundation; - Learn the practical applications; - Gain a comprehensive understanding of distributed systems with real-world examples; - Get clarity; - Say goodbye to confusion and uncertainty as you master distributed systems with clear explanations. This book is designed for software engineers looking to learn about distributed systems and climb the ladder from beginner to expert.

Название: Python Programming
Автор: S. Sridhar, J. Indumathi, V.M. Hariharan
Издательство:‎ Pearson Education
Год: 2023
Страниц: 794
Язык: английский
Формат: epub
Размер: 20.2 MB

Python Programming is designed to be a textbook for undergraduate and postgraduate students to provide programming knowledge and enhance problem-solving skills. The book begins with the basics of Python programming followed by the basics of algorithms and further focuses on topics like introduction to programming language, looping, functions, and data structures like lists, tuples, sets, dictionary, and strings. It covers functional programming concepts such as higher-order functions. It also covers Object Oriented Programming concepts such as inheritance and polymorphism. The book also deals with modules and packages, errors and exceptions, Python testing, profiling, debugging, and file handling. The book then focuses on GUI programming. An introduction to data analytics, databases, network programming, and security is provided in this book. The book is also helpful for diploma courses, school curricula, competitive examinations like GATE, coding interviews, and coding competitions. This book can also be used for imparting training and certificate courses to professionals. This book is also ideal for self-study who wishes to make a career in the IT field. Whether a beginner or an experienced coder, this book will help readers navigate through Python and enable them to maximize its power, versatility, and general-purpose nature as a programming language.

Название: Python in Excel: Boost Your Data Analysis and Automation with Powerful Python Scripts
Автор: Hayden Van Der Post
Издательство: Reactive Publishing
Год: 2024
Страниц: 769
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Unlock the Full Potential of Excel with Python Integration. Transform your data analysis and automation tasks with "Python in Excel: Boost Your Data Analysis and Automation with Powerful Python Scripts." This groundbreaking guide combines the versatility of Python programming with the robust functionalities of Excel, empowering you to elevate your spreadsheet game like never before. Excel is renowned for its user-friendly interface and powerful built-in functionalities. However, it has limitations when dealing with large datasets, performing complex calculations, or automating repetitive tasks. Python complements Excel by offering extensive libraries such as Pandas, NumPy, and Matplotlib, which are designed for data manipulation, numerical computations, and visualization. This integration can mitigate Excel's limitations, providing a robust platform for comprehensive data analysis. Python excels in data manipulation with its Pandas library, which simplifies tasks like filtering, grouping, and aggregating data. This can be particularly useful in cleaning and preparing data before analysis. Join the Data Revolution: With "Python in Excel: Boost Your Data Analysis and Automation with Powerful Python Scripts," you’ll harness the power of Python to transform your Excel experience. Embrace the future of data analysis and automation with this essential guide.

Название: Programming for Corpus Linguistics with Python and Dataframes
Автор: Daniel Keller
Издательство: Cambridge University Press
Год: 2024
Страниц: 114
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

This Element offers intermediate or experienced programmers algorithms for Corpus Linguistic (CL) programming in the Python language using dataframes that provide a fast, efficient, intuitive set of methods for working with large, complex datasets such as corpora. This Element demonstrates principles of dataframe programming applied to CL analyses, as well as complete algorithms for creating concordances; producing lists of collocates, keywords, and lexical bundles; and performing key feature analysis. An additional algorithm for creating dataframe corpora is presented including methods for tokenizing, part-of-speech tagging, and lemmatizing using spaCy. This Element provides a set of core skills that can be applied to a range of CL research questions, as well as to original analyses not possible with existing corpus software.