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Название: A Common-Sense Guide to Data Structures and Algorithms in jаvascript: Level Up Your Core Programming Skills, Volume 1
Автор: Jay Wengrow
Издательство: Pragmatic Bookshelf
Год: August 2024 (P1.0)
Страниц: 516
Язык: английский
Формат: True EPUB (Retail Copy)
Размер: 19.99 MB

If you thought data structures and algorithms were all just theory, you're missing out on what they can do for your jаvascript code. Learn to use Big O notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. Every chapter features practice exercises to give you the hands-on information you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. The jаvascript edition uses jаvascript exclusively for all code examples, exercises, and solutions. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions. Use these techniques today to make your jаvascript code faster and more scalable.

Название: Harnessing Python for Generative AI
Автор: Anand Vemula
Издательство: Independently published
Год: 2024
Страниц: 156
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

This book covers the fundamentals of generative AI, providing an in-depth understanding of key concepts, algorithms, and techniques that power AI-driven content creation. Starting with an introduction to the basics of Generative AI, the book explains the theoretical foundations and evolution of generative models, highlighting the significance of this technology in various domains such as image synthesis, text generation, and more. Readers will explore the different types of Machine Learning, including supervised, unsupervised, and reinforcement learning, and understand their role in the development of generative models. The guide dives into essential Python libraries like TensorFlow, PyTorch, NumPy, and Pandas, offering a hands-on approach to building generative models from scratch. Each chapter is packed with practical examples, case studies, and real-world scenarios that demonstrate the application of these models in various fields, including art, music, and conversational AI. Key topics include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), flow-based models, autoregressive models, and transformer-based models like GPT. The book also addresses the ethical considerations surrounding generative AI, providing insights into the challenges of bias, fairness, and misinformation. Readers will benefit from step-by-step tutorials that guide them through the process of implementing and optimizing generative models, complete with code examples and hands-on exercises. Additionally, the book offers advanced techniques for improving model performance and stability, ensuring that readers are well-prepared to tackle complex AI projects. Whether you're a beginner looking to understand the basics of Generative AI or an experienced developer aiming to enhance your skills, "Mastering Generative AI with Python: A Hands-On Guide" serves as an essential resource for anyone interested in the rapidly evolving field of Generative AI.

Название: Серия "Библиотека специалиста" в 8 книгах
Автор(ы): разные
Издательство: Питер
Год: 2011-2025
Страниц: 1000+
Формат: pdf, fb2
Размер: 120 Мб
Язык: русский

В серию "Библиотека специалиста" входит техническая литература и пособия по программированию и работе в интернете. В пособиях по программированию вы найдете ряд практических советов по изучению и применению на практике основных языков. Программисты делятся своими знаниями по стандартам и особенностям каждого языка, использованию функциональных возможностей в полной мере.
Так как пособия написаны работающими в этой сфере специалистами, в книгах практически нет теоретических выкладок, все понятия, способы кодировки даны на примерах и задачах.

Название: CompTIA Tech+ Study Guide: Exam FC0-U71 (Sybex Study Guide), 3rd Edition
Автор: Quentin Docter
Издательство: Sybex
Год: 2025
Страниц: 771
Язык: английский
Формат: pdf (true)
Размер: 30.3 MB

An easy-to-read and authoritative new study guide for the updated CompTIA Tech+ certification exam. In the newly updated third edition of the CompTIA Tech+ Study Guide: Exam FC0-U71, veteran IT professional and tech trainer Quentin Docter delivers an up-to-date resource for effectively and efficiently preparing for the popular new introductory Tech+ certification from CompTIA. This Sybex Study Guide is the gold-standard exam prep roadmap, offering complete coverage of every exam domain, including IT concepts and terminology, infrastructure, applications and software development, data and database fundamentals, security, and more. Perfect for practicing and aspiring entry-level IT pros as well as those preparing to take the CompTIA Tech+ test, this book includes complementary access to online learning resources, two practice exams, flashcards, and practice questions with answer explanations. The new, entry-level CompTIA Tech+ certification has been created to get you ready for further certification paths, like the A+, Security+, and Network+ credentials, and prepare you for an exciting career in tech. Whether you're an IT beginner or you've already begun your tech journey and are looking for a refresher on foundational concepts, CompTIA Tech+ Study Guide: Exam FC0-U71 is the book you've been waiting for.

Название: Artificial Intelligence and Machine Learning with R: Applications in the Field of Business Analytics
Автор: Bernd Heesen
Издательство: Springer
Год: 2024
Страниц: 503
Язык: английский
Формат: pdf (true), epub
Размер: 50.6 MB

In a VUCA world, which is becoming increasingly volatile, uncertain, and complex, companies, organizations, and states must respond promptly and adequately to the respective situations. Making decisions based on past experiences is less successful in these times than having an accurate understanding of current conditions. The importance of empirical sciences, continuous environmental observation, timely analysis of causal relationships, and deriving new insights from them is increasing. From this, it can be deduced which measures are likely to achieve one's goals with predictable probability, such as which price for an offer generates the desired demand or which marketing measure reaches the desired target group. Where classical statistics were once used for calculations and predictions, today free (open source) tools like R allow data in various formats and from any number of sources to be read in, processed, and analyzed using methods of Artificial Intelligence (AI) and Machine Learning (ML). The results can then be perfectly visualized so that decision-makers can benefit quickly and effectively. The age of Data Science has arrived. Digitalization is more than a buzzword or a promise; it is actionable and usable for everyone. This book teaches you, based on the latest version of R at the time of publication, how to use Artificial Intelligence and Machine Learning in Industry 4.0.

Название: The Quick Guide to Prompt Engineering: Generative AI Tips and Tricks for ChatGPT, Bard, Dall-E, and Midjourney
Автор: Ian Khan
Издательство: Wiley
Год: 2024
Страниц: 479
Язык: английский
Формат: pdf (true), epub (true)
Размер: 10.1 MB

Design and use Generative AI prompts that get helpful and practical results in this concise and quick start guide. In The Quick Guide to Prompt Engineering, renowned technology futurist and AI thought leader Ian Khan delivers a practical and insightful resource for taking the first steps in understanding and learning how to use Generative AI. You will learn how to design and use prompts to get the most out of Large Language Model generative AI applications like ChatGPT, DALL-E, Google’s Bard, and explore how to understand Generative Artificial Intelligence and how to engineer prompts in a wide variety of industry use cases. You’ll also find illuminating case studies and hands-on exercises, as well as step-by-step guides, to get you up to speed on prompt engineering in no time at all. The book has been written for the non-technical user to take the first steps in the world of Generative AI. Codex represents not merely the next iteration of code-generation tools but an avant-garde transformation of how we perceive the confluence of coding and AI. At its essence, Codex is a prodigious language model specifically designed for generating code, and its inception can be considered both an evolution and a revolution. Codex's lineage traces back to the landmark achievements of its predecessors, particularly GPT-3, one of Open AI's most lauded creations. While GPT-3 demonstrated awe-inspiring abilities across a wide range of natural language processing tasks, Codex fine-tunes this prowess with an emphasis on code generation.

Название: Large Language Models: An Introduction
Автор: Oswald Campesato
Издательство: Mercury Learning and Information
Год: 2024
Страниц: 542
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

This book begins with an overview of the Generative AI landscape, distinguishing it from conversational AI and shedding light on the roles of key players like DeepMind and OpenAI. It then reviews the intricacies of ChatGPT, GPT-4, Meta AI, Claude 3, and Gemini, examining their capabilities, strengths, and competitors. Readers will also gain insights into the BERT family of LLMs, including ALBERT, DistilBERT, and XLNet, and how these models have revolutionized natural language processing. Further, the book covers prompt engineering techniques, essential for optimizing the outputs of AI models, and addresses the challenges of working with LLMs, including the phenomenon of hallucinations and the nuances of fine-tuning these advanced models. Designed for software developers, AI researchers, and technology enthusiasts with a foundational understanding of AI, this book offers both theoretical insights and practical code examples in Python. This book is intended primarily for people who have a basic knowledge of Generative AI or software developers who are interested in working with LLMs. Specifically, this book is for readers who are accustomed to searching online for more detailed information about technical topics.

Название: Kickstart Software Design Architecture: Transform Your Software Development Journey with Key Principles and Advanced Practices in Architecture, Microservices, and Cloud Computing
Автор: Edward D Lavieri Jr.
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 356
Язык: английский
Формат: epub (true)
Размер: 17.9 MB

Learn to design robust software systems using modern architecture principles and practical hands-on experience. Kickstart Software Design Architecture is designed to empower readers with a deep understanding of software architecture's critical role in successful software development. Firstly, the book offers interactive exercises, allowing readers to apply principles in real-world scenarios, thereby solidifying their understanding of how software architecture directly impacts the efficiency, scalability, and maintainability of applications. Secondly, through an extensive collection of case studies and examples, it provides industry's best practices, demonstrating the influence of well-designed software architecture on a project’s success. Explore the ever-evolving world of software architecture. The book highlights the significance of software architecture in building scalable, efficient, and robust applications. The book is structured into engaging chapters, each focused on a specific aspect of software architecture. It starts with an introduction to the basics of software design patterns, gaining an understanding of their role in crafting flexible and reusable code. Next, microservices are covered, followed by chapters that focus on cloud computing, containerization, and more. Chapters contain real-world examples, hands-on exercises, and case studies, to help readers gain both foundational knowledge and hands-on experience. By the end of the book, you should have a solid foundation in software architecture and be equipped with the knowledge and skills to confidently address complex software architectural challenges. The Chapter 3 explores the impact of programming languages on software design by comparing Java and Python, highlighting their unique architectural considerations, and discussing best practices for coding in each language.

Название: Large Language Models Projects: Apply and Implement Strategies for Large Language Models
Автор: Pere Martra
Издательство: Apress
Год: 2024
Страниц: 366
Язык: английский
Формат: pdf
Размер: 12.0 MB

This book offers you a hands-on experience using models from OpenAI and the Hugging Face library. You will use various tools and work on small projects, gradually applying the new knowledge you gain. The book is divided into three parts. Part one covers techniques and libraries. Here, you'll explore different techniques through small examples, preparing to build projects in the next section. You'll learn to use common libraries in the world of Large Language Models. Topics and technologies covered include chatbots, code generation, OpenAI API, Hugging Face, vector databases, LangChain, fine tuning, PEFT fine tuning, soft prompt tuning, LoRA, QLoRA, evaluating models, and Direct Preference Optimization. Part two focuses on projects. You'll create projects, understanding design decisions. Each project may have more than one possible implementation, as there is often not just one good solution. You'll also explore LLMOps-related topics. Part three delves into enterprise solutions. Large Language Models are not a standalone solution; in large corporate environments, they are one piece of the puzzle. You'll explore how to structure solutions capable of transforming organizations with thousands of employees, highlighting the main role that Large Language Models play in these new solutions. For Data analysts, Data Science, Python developers, and software professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.

Название: Mathematical Modeling for Computer Applications
Автор: Biswadip Basu Mallik, M. Niranjanamurthy, Sharmistha Ghosh, Valentina Emilia Balas, Krishanu Deyasi, Santanu Das
Издательство: Wiley-Scrivener
Серия: Mathematics and Computer Science
Год: 2024
Страниц: 546
Язык: английский
Формат: pdf (true)
Размер: 46.1 MB

This new volume in this groundbreaking series on mathematics and computer science builds on the basic concepts and fundamentals laid out in previous volumes, presenting the reader with more advanced and cutting-edge topics being developed in this exciting field. Mathematics is the foundation on which Computer Science is built. Mathematical Logic, Set theory, Combinatorics, Graph Theory, Probability Theory, Number Theory, and Algebra are all part of Discrete Mathematics and form the basic foundation for Programming and Computer Science. Analytical skills are a necessity for learning problem-solving and data analysis. And, mathematics is the first place where you get to use these skills. Computer science examines the principles and use of computers in processing information, designing hardware and software, and using applications. Algebra is used in computer science in the development of algorithms and software for working with mathematical objects. It is also used to design formulas that are used in numerical programs and for complete scientific computations. Statistics is a form of mathematics used in Computer Science that uses quantified models, representations, and synopses for a provided collection of experimental data or actual studies. The field studies methodologies to obtain, review, evaluate, and form conclusions from data. Statistics is used for data mining, speech recognition, vision and image analysis, data compression, traffic modelling, and even Artificial Intelligence (AI) and for simulations.