Все для школьников, студентов, учащихся, преподавателей и родителей - Обучалка - Obuchalka.org

ChatGPT каждый день, Библиотека промптов для задач и решений, Костин А.А., 2026.

   Вы открываете ChatGPT. задаёте вопрос и получаете длинный, размытый ответ, который приходится переписывать, уточнять и переделывать. В итоге время тратится не меньше, чем без нейросети. Причина проста: большинство людей работают с ChatGPT без системы. В этой книге собрана практическая библиотека из сотен готовых промптов для реальных задач: планирование дня и недели, деловые письма, управление проектами, анализ решений, контроль качества, антикризисный режим. Вместо хаотичных экспериментов вы получите чёткую структуру: как выбирать правильный запрос, какие переменные указывать, как улучшать результат без переписывания и как превращать ответы нейросети в готовые решения. Эта книга поможет сократить время на формулировки, уменьшить количество переделок и превратить ChatGPT в рабочий инструмент, который экономит часы каждую неделю.

GPT Meets Game Theory, Training and Optimizing Generative AI Models, Tembine H., 2026.

   GPT Meets Game Theory offers an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models, particularly transformers, and also for those who are curious about how game theory can apply to the training and optimisation of these models.

Google Gemini For Beginners, Get started with Google's AI companion, 2026.

   Al, Artificial Intelligence, has evolved significantly over the last decade. Where once it was perceived as something we'd probably only achieve in the next hundred years or so, it's now believed that true Al is, in all likelihood, just a few years away. And despite that scaring the socks off many fu^msts, it may astonish you to discover that Al is already here.

Generative AI, Geetha T.V.

   Generative AI discusses the basics of generative AI, classification and types of deep models, applications, tools, evaluation and ethical perspectives of generative AI and hence enables learners to understand the mystic of generative AI from both academic and industry perspectives. An introduction on the connection between AI, machine learning, deep learning and generative AI is explained. The mathematical foundations required to assimilate deep generative models and their classification are discussed next. The book then goes onto to discuss various generative AI models including autoregressive models, variational autoencoders, generative adversarial networks, diffusion models, flow-based and energy based generative models and transformer models in detail. It also explains pre-trained language models and large language models including fine-tuning, prompt engineering and popular large language models such as GPT, BERT, T5, BART and EMO architectures. The book then discusses the varied applications of generative AI text, audio, conversational, image and video models and domain based applications in healthcare, advertising and marketing, manufacturing, finance, media and entertainment and education. The book also outlines the various tools available. The book also gives an overview of evaluation of generative AI and the ethical perspectives associated with generative AI. In addition, many exercises and activities are included to enable the reader understand concepts and apply them to build meaningful applications using the latest techniques.

Deep Learning, Sridhar S., Narashiman D.

   Deep Learning is designed to be a textbook for undergraduate and postgraduate students. Many Indian universities have started giving UG courses in Artificial Intelligence, Machine Learning, and Data Science. This book would be helpful for computer science and IT students who specialize in these degrees. The book aims to provide basics like artificial intelligence, machine learning, natural language processing, image processing, and computer vision that are necessary to understand deep learning technologies. The concepts of basic neural networks are discussed along with activation and loss functions. The concept of optimization and regularization are dealt with in this book.

Create your online store with Django 5, Yoris A.C., 2025.

   This book was written by Andres Cruz Yoris, a graduate in Computer Science with over 10 years of experience developing web applications in general. I work with PHP, Python, and client-side technologies such as HTML, JavaScript, CSS, Vue, and others; and server-side technologies such as Laravel, Flask, Django, and CodeIgniter. I'm also a developer in Android Studio, xCode, and Flutter for creating native applications for Android and iOS.
I share some of my learning experience with you, reflected in each of the words that make up this book, my second book on Django; this time a more advanced, mid-professional-level book.

Cognitive Kin, How to Work, Win, and Make Meaning with Agentic AI, Kolb C., Rosen J., 2026.

   Cognitive Kin does not offer a simple playbook, but it provides a rigorous framework for thinking about these issues. It calls for a mindset grounded in curiosity, disciplined experimentation, and alignment with human values. Progress in AI will depend on leaders who understand that trust, governance, and accountability are as critical as innovation itself.
This book is a timely contribution to that conversation. It invites us to approach AI not as a force to be managed, but as a relationship to be shaped. The opportunity ahead lies in learning how to evolve with intelligent systems, creating new forms of collaboration that enhance both human and organizational potential.

Claude Code, Полное руководство по AI-ассистенту для разработчиков, Мукминов Р., 2026.
 
   Уважаемый читатель, перед вами – наиболее полное русскоязычное руководство по Claude Code, революционному AI-ассистенту для разработчиков, созданному компанией Anthropic. Эта книга родилась из простого наблюдения: мир программирования переживает фундаментальный сдвиг, сопоставимый по масштабу с появлением объектно-ориентированного программирования, открытого программного обеспечения или облачных вычислений. Искусственный интеллект больше не является экзотической технологией из научно-фантастических фильмов – он превратился в повседневный инструмент, способный кардинально изменить то, как мы пишем, отлаживаем и поддерживаем программный код.