Название: AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment
Автор: Тоm Таulli
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 225
Язык: английский
Формат: pdf (true)
Размер: 10.87 MB

Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. The Chapter 1 kicks off with a look into how generative AI is changing the game for coders. It talks about how these AI tools are helping developers think more about the big picture and less about the nitty-gritty of coding. The chapter also takes a stroll through the history of programming languages. There are also details about the advanced AI technologies like GPT-4. This book is for any developer, whether you’re just starting out or you’ve been in the game for many years.

Название: Effective Rust: 35 Specific Ways to Improve Your Rust Code
Автор: Dаvid Drуsdаlе
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 296
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Rust's popularity is growing, due in part to features like memory safety, type safety, and thread safety. But these same elements can also make learning Rust a challenge, even for experienced programmers. This practical guide helps you make the transition to writing idiomatic Rust—while also making full use of Rust's type system, safety guarantees, and burgeoning ecosystem. If you're a software engineer who has experience with an existing compiled language, or if you've struggled to convert a basic understanding of Rust syntax into working programs, this book is for you. By focusing on the conceptual differences between Rust and other compiled languages, and by providing specific recommendations that programmers can easily follow, Effective Rust will soon have you writing fluent Rust, not just badly translated C++. In the crowded landscape of modern programming languages, Rust is different. Rust offers the speed of a compiled language, the efficiency of a non-garbage-collected language, and the type safety of a functional language—as well as a unique solution to memory safety problems. As a result, Rust regularly polls as the most loved programming language. This book tries to help with these areas where programmers struggle, even if they already have experience with an existing compiled language like C++.

Название: Jetpack Compose 1.6 Essentials: Developing Android Apps with Jetpack Compose 1.6, Android Studio, and Kotlin
Автор: Nеil Smуth
Издательство: Payload Media
Год: 2024
Страниц: 1057
Язык: английский
Формат: epub
Размер: 38.3 MB

This book teaches you how to build Android applications using Jetpack Compose 1.6, Android Studio Iguana (2023.2.1), Material Design 3, and the Kotlin programming language. The book begins with the basics by explaining how to set up an Android Studio development environment. The book also includes in-depth chapters introducing the Kotlin programming language, including data types, operators, control flow, functions, lambdas, coroutines, and object-oriented programming. An introduction to the key concepts of Jetpack Compose and Android project architecture is followed by a guided tour of Android Studio in Compose development mode. The book also covers the creation of custom Composables and explains how functions are combined to create user interface layouts, including row, column, box, flow, pager, and list components. Other topics covered include data handling using state properties and key user interface design concepts such as modifiers, navigation bars, and user interface navigation. Additional chapters explore building your own reusable custom layout components, securing your apps with Biometric authentication, and integrating Google Maps. The book covers graphics drawing, user interface animation, transitions, Kotlin Flows, and gesture handling.

Название: Build a Frontend Web Framework (From Scratch) (MEAP v11)
Автор: Аngеl Sоlа Оrbаiсеtа
Издательство: Manning Publications
Год: 2024
Страниц: 527
Язык: английский
Формат: pdf, epub
Размер: 28.0 MB

Learn how a frontend web framework works by coding your own! In Build a Frontend Web Framework (From Scratch), you’ll learn the secrets behind frameworks like React, Vue, and Angular. Frontend frameworks are essential for creating websites, UIs, and intuitive apps. While it’s tempting to treat a framework like a black box, they’re not magic. Build a Frontend Web Framework (From Scratch) shows you how to build your own framework from basic javascript, HTML, and CSS. Once you learn how frameworks function, you’ll be able to work with them more efficiently, troubleshoot bugs more effectively, and even customize them for your specific needs. Frontend web frameworks like React, Vue, or Svelte are an essential part of almost any web application stack.

Название: Generative AI in Action (MEAP v5)
Автор: Аmit Ваhrее
Издательство: Manning Publications
Год: 2024
Страниц: 266
Язык: английский
Формат: epub
Размер: 39.7 MB

Generative AI can transform your business by streamlining the process of creating text, images, and code. This book will show you how to get in on the action! Generative AI has created new opportunities for organizations of all sizes. You can easily use tools like ChatGPT, Bard, and Stable Diffusion to generate text and images for product catalogs, marketing campaigns, technical reporting, and other common tasks. Coding assistants like Copilot are accelerating productivity in software teams. In this insightful book, author Amit Bahree shares his experience leading Generative AI projects at Microsoft for nearly a decade, starting well before the current GPT revolution. Generative AI in Action shows you exactly how to add generative AI tools for text, images, and code, and more into your organization’s strategies and projects. The book begins with the fundamentals of generative AI models and architectures, and introduces practical use-cases to create efficient processes for marketing, software development, business report generation and other practical tasks. You’ll quickly master best practices for prompt engineering, model fine tuning and evaluation, and explore the emerging architecture patterns that support generative AI in your enterprise workflow. Along the way, you’ll explore important facts about AI safety and ethics, and look ahead to new trends such as explainable AI, transfer learning, and reinforcement learning. With a frank discussion of risks like hallucinations and jailbreaks, Generative AI in Action gives you the insight you need to incorporate these powerful technologies with confidence. For enterprise architects and senior developers interested in upgrading their architectures with generative AI.

Название: Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications 2nd Edition
Автор: Lаurа Iguаl, Sаnti Sеguі
Издательство: Springer
Серия: Undergraduate Topics in Computer Science
Год: 2024
Страниц: 255
Язык: английский
Формат: pdf
Размер: 10.1 MB

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of Data Science. The coverage spans key concepts from statistics, Machine Learning/Deep Learning and responsible Data Science, useful techniques for network analysis and natural language processing (NLP), and practical applications of Data Science such as recommender systems or sentiment analysis. This book includes three different kinds of chapters. The first kind is about Python extensions. Python was originally designed to have a minimum number of data objects (int, float, string, etc.); but when dealing with data, it is necessary to extend the native set to more complex objects such as (NumPy) numerical arrays or (Pandas) data frames. The second kind of chapter includes techniques and modules to perform statistical analysis and Machine Learning. Finally, there are some chapters that describe several applications of Data Science, such as building recommenders or sentiment analysis. The composition of these chapters was chosen to offer a panoramic view of the Data Science field, but we encourage the reader to delve deeper into these topics and to explore those topics that have not been covered: big data analytics and more advanced mathematical and statistical methods (e.g., Bayesian statistics). This book is addressed to upper-tier undergraduate and beginning graduate students from technical disciplines. Moreover, this book is also addressed to professional audiences following continuous education short courses and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required. Code programming in Python is of benefit.

Название: Causal AI (MEAP v9)
Автор: Rоbеrt Оsаzuwа Nеss
Издательство: Manning Publications
Год: 2024
Страниц: 576
Язык: английский
Формат: epub
Размер: 39.0 MB

How do you know what might have happened, had you done things differently? Causal Machine Learning gives you the insight you need to make predictions and control outcomes based on causal relationships instead of pure correlation, so you can make precise and timely interventions. Causal Machine Learning is a major milestone in Machine Learning, allowing AI models to make accurate predictions based on causes rather than just correlations. Causal techniques help you make models that are more robust, explainable, and fair, and have a wide range of applications, from improving recommendation engines to perfecting self-driving cars. Causal AI teaches you how to build Machine Learning and Deep Learning models that implement causal reasoning. Discover why leading AI engineers are so excited by causal reasoning, and develop a high-level understanding of this next major trend in AI. New techniques are demonstrated with example models for solving industry-relevant problems. You’ll learn about causality for recommendations; causal modeling of online conversions; and uplift, attribution, and churn modeling. Each technique is tested against a common set of problems, data, and Python libraries, so you can compare and contrast which will work best for you. For data scientists and Machine Learning engineers. A familiarity with probability and statistics will be helpful, but not essential, to begin this guide. Examples in Python.

Название: Hacking Cryptography: Write, break, and fix real-world implementations (MEAP v9)
Автор: Каmrаn Кhаn, Вill Сох
Издательство: Manning Publications
Год: 2024
Страниц: 262
Язык: английский
Формат: pdf (true)
Размер: 16.6 MB

Learn how the good guys implement cryptography and how the bad guys exploit it. Theoretically strong cryptography often becomes vulnerable to exploitation as soon as it’s built into real applications and networks. Hacking Cryptography details dozens of practical cryptographic implementations and then breaks down the flaws that adversaries use to exploit them. You’ll learn just what it takes to write cryptographically secure code, build an intuition for spotting potential vulnerabilities, and master techniques to avoid the pitfalls that leave your systems at risk. Hacking Cryptography builds your understanding of cryptography by revealing the “lockpicks” that bad actors use to exploit security protocols, firewalls, and other cryptography-based protection schemes. The book dives deep into each cryptographic exploit, explaining complex concepts in detail through real-world analogies, code annotations, and pseudo-code. You’ll explore historical examples where popular cryptography has failed, such as the breaking of the WEP protocol, and see what impact those failures have had on modern cryptography. For software and security engineers. No advanced mathematical knowledge required. Examples in Go.

Название: Probabilistic Indexing for Information Search and Retrieval in Large Collections of Handwritten Text Images
Автор: Аlеjаndrо Несtоr Тоsеlli, Jоаn Рuigсеrvеr, Еnriquе Vidаl
Издательство: Springer
Год: 2024
Страниц: 372
Язык: английский
Формат: pdf (true)
Размер: 13.2 MB

This book provides a comprehensive presentation of a recently introduced framework, named "probabilistic indexing" (PrIx), for searching text in large collections of document images and other related applications. It fosters the development of new search engines for effective information retrieval from manuscripts which, however, lack the electronic text (transcripts) that would typically be required for such search and retrieval tasks. The book is structured into 11 chapters and three appendices. The first two chapters briefly outline the necessary fundamentals and state of the art in pattern recognition, statistical decision theory, and handwritten text recognition. Chapter 3 presents approaches for indexing (as opposed to “spotting”) each region of a handwritten text image which is likely to contain a word. Next, Chapter 4 describes models adopted for handwritten text in images, namely hidden Markov models, convolutional and recurrent neural networks and language models, and provides full details of weighted finite-state transducer (WFST) concepts and methods, needed in further chapters of the book. Chapter 5 explains the set of techniques and algorithms developed to generate image probabilistic indexes which allow for fast search and retrieval of textual information in the indexed images. This book is written for researchers and (post-)graduate students in pattern recognition and information retrieval.

Название: Deep Learning Models: A Practical Approach for Hands-On Professionals
Автор: Jоnаh Gаmbа
Издательство: Springer
Год: 2024
Страниц: 211
Язык: английский
Формат: pdf (true), epub
Размер: 65.3 MB

This book focuses on and prioritizes a practical approach, minimizing theoretical concepts to deliver algorithms effectively. With Deep Learning emerging as a vibrant field of research and development in numerous industrial applications, there is a pressing need for accessible resources that provide comprehensive examples and quick guidance. Unfortunately, many existing books on the market tend to emphasize theoretical aspects, leaving newcomers scrambling for practical guidance. This book takes a different approach by focusing on practicality while keeping theoretical concepts to a necessary minimum. The book begins by laying a foundation of basic information on Deep Learning, gradually delving into the subject matter to explain and illustrate the limitations of existing algorithms. A dedicated chapter is allocated to evaluating the performance of multiple algorithms on specific datasets, highlighting techniques and strategies that can address real-world challenges when Deep Learning is employed. The Chapter 2 introduce some of the concepts needed to start building Deep Learning models in Python. The chapter starts with basic principles related to data manipulation and ends with explanation on how to set up the modelling environment. It is expected that the reader is familiar with some high-level programming concepts which are very easy to acquire within a short space of time. Deep Learning models mostly deal with vectors and matrices as we know them from linear algebra. This book is designed to equip professionals with the necessary skills to thrive in the active field of Deep Learning, where it has the potential to revolutionize traditional problem-solving approaches.