Книги по GPT/AI/ИИ

 Ежедневно в мире происходит более 2 тысяч кибератак. Кибербезопасность входит в число отраслей, которым в ближайшие 5 лет прогнозируют невероятный рост. Она обеспечивает защиту компьютерных систем, сетей, программ и данных от киберугроз (хакерских атак, вирусов, вредоносного ПО и др.). Несмотря на полезность искусственного интеллекта, не следует игнорировать факт, что технологии искусственно...

Learn JavaScript Smarter and Faster! Step into the future of coding with this comprehensive guide to mastering JavaScript. Combining essential programming concepts with AI tools and visual aids, this book is designed for beginners to help you grasp even the most complex ideas quickly and efficiently.Why Choose This Book?Master JavaScript with Carefully Designed Content: This book offers compr...

 The AI Revolution is Here. Discover its Dynamic Applications in Networking, Cybersecurity, and More. AI is having a profound impact on nearly every sector of the workforce. Huge professional and financial opportunities await in the key domains of computer networking, cybersecurity, IoT, and cloud computing. The AI Revolution in Networking, Cybersecurity, and Emerging Technologies will g...

 This practical book offers clear, example-rich explanations of how LLMs work, how you can interact with them, and how to integrate LLMs into your own applications. Find out what makes LLMs so different from traditional software and ML, discover best practices for working with them out of the lab, and dodge common pitfalls with experienced advice. In LLMs in Production you will:Grasp the...

 Automated digital financial advisors—also called robo-advisors—manage billions of dollars in assets. Follow the step-by-step instructions in this hands-on guide, and you’ll learn to build your robo-advisor capable of managing a real investing strategy. In Build a Robo-Advisor with Python (From Scratch) you’ll learn how to:Measure returns and estimate the benefits of robo-advisorsUse Mon...

 In today’s world, understanding data analytics, data science, and artificial intelligence is not just an advantage but a necessity. This book is your thorough guide to learning these innovative fields, designed to make the learning practical and engaging.  The book starts by introducing data analytics, data science, and artificial intelligence. It illustrates real-world application...

 This book explores how to define, design, and maintain enterprise AI applications, exploring the impacts they will have on the teams who work with them. The book is structured into four parts. In Part 1: Defining Your AI Application, you are introduced to the dynamic interplay between human adaptability and AI specialization, the concept of meta systems, and the mechanics of prediction...

 Delivering effective search is one of the biggest challenges you can face as an engineer. AI-Powered Search is an in-depth guide to building intelligent search systems you can be proud of. It covers the critical tools you need to automate ongoing relevance improvements within your search applications. Inside you’ll learn modern, data-science-driven search techniques like: Semantic...

 The era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you’ll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications. The chapters will help you discover best practices for data preparatio...

 Despite promising advances, the opaque nature of deep learning models makes it difficult to interpret them, which is a drawback in terms of their practical deployment and regulatory compliance. Deep Learning and XAI Techniques for Anomaly Detection shows you state-of-the-art methods that'll help you to understand and address these challenges. By leveraging the Explainable AI (XAI) and d...

 “Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers...

 Эта небольшая книга представляет собой подробное руководство для разработчиков на Python, желающих научиться создавать приложения с использованием больших языковых моделей. Авторы расскажут об основных возможностях и преимуществах GPT-4 и ChatGPT, а также принципах их работы. Здесь же вы найдете пошаговые инструкции по разработке приложений с использованием библиотеки поддержки GPT-4 и ChatG...

 Data labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today's data-driven world, mastering data labeling is not just an advantage, it's a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution.  ...

 This book is designed to bridge the gap between theoretical knowledge and practical application in the fields of Python programming, machine learning, and the innovative use of ChatGPT-4 in data science. The book is structured to facilitate a deep understanding of several core topics. It begins with a detailed introduction to Pandas, a cornerstone Python library for data manipulation and ana...

 Генеративный ИИ — одна из самых обсуждаемых тем в сфере технологий. Пора разобраться с возможностями TensorFlow и Keras, чтобы с легкостью создавать впечатляющие генеративные модели глубокого обучения, включая вариационные автокодировщики (VAE), генеративно-состязательные сети (GAN), трансформеры, нормализующие потоки, модели на основе энергии и диффузионные модели удаления шума. Дэвид...