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Посты канала
| 2 | Sutskever's List: Foundational ideas of modern AI (Final Release) 2026
Автор: Richard Heimann
"A perspective the field has needed. Sutskever’s List delivers it with care and historical accuracy.” - Yanping Huang, Google
Sutskever’s List is a guided intellectual journey through the ideas that made modern AI suddenly possible. Each chapter is anchored in specific papers, books, or other sources from Sutskever’s list. The papers themselves are not the focus. Instead, the author uses them as entry points into the larger breakthroughs, arguments, interconnections, and shifts in thinking that transformed the field.
It begins with AlexNet, where data, GPUs, and training craft made neural networks impossible to dismiss, then moves to ResNet, where depth becomes a superpower rather than a liability. From there, the story accelerates through sequence models, speech systems, attention, Transformers, and hyperscale, showing how AI escaped older bottlenecks and became built to grow. | 345 |
| 3 | Fabulous Adventures in Data Structures and Algorithms_Final.pdf | 615 |
| 4 | Fabulous Adventures in Data Structures and Algorithms (Final) 2026
Автор: Eric Lippert
Fabulous Adventures in Data Structures and Algorithms invites you to step off the beaten path and explore interesting, unfamiliar, and even exotic algorithms that will challenge your perspective and elevate your code. Legendary language designer Eric Lippert guides you with a refreshing, conversational approach, providing beautifully practical examples that highlight the recurring patterns behind stubborn coding problems.
You’ll begin with a fresh look at foundational, thread-safe, and persistent immutable data structures. Lippert demystifies stacks, queues, and finger-tree deques, illustrating how to manage memory efficiently through persistence. For developers working in highly concurrent, cloud native environments, these patterns will help you eliminate hard-to-spot race conditions and state-mutation bugs. | 546 |
| 5 | Java in a Nutshell 9Ed_Final.pdf | 840 |
| 6 | Java in a Nutshell: A Desktop Quick Reference, 9th Edition (Final Release) 2026
Автор: Benjamin J. Evans
Java in a Nutshell doesn't just help experienced Java programmers get the most out of versions through Java 25. It also provides a learning path for new developers. Chock-full of examples that demonstrate how to take complete advantage of modern Java APIs and development best practices, this thoroughly revised guide includes new material on recent enhancements to Java. | 778 |
| 7 | Causal Inference for Data Science_True.pdf | 874 |
| 8 | Causal Inference for Data Science (Final Release) 2026
Автор: Aleix Ruiz de Villa Robert
When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and Machine Learning.
A/B tests or randomized controlled trials are expensive and often unfeasible in a business environment. Causal Inference for Data Science reveals the techniques and methodologies you can use to identify causes from data, even when no experiment or test has been performed. | 811 |
| 9 | Python Projects for Raspberry Pi_True.pdf | 823 |
| 10 | Python Projects for Raspberry Pi: Physical computing for work, play, and learning 2026
Автор: Ben Everard
Build projects using Raspberry Pi hardware that interacts with our real world.
Computers are embedded into almost everything we own. Our doorbells, kitchen gadgets, vacuum cleaners, and media players are all powerful computing devices running software that someone has written.
Using the flexible Python programming language, Python Projects for Raspberry Pi shows you how to get the most out of the Pico range of microcontrollers and Raspberry Pi computers like Raspberry Pi 5. | 779 |
| 11 | Recursion Mathematics and Python.pdf | 903 |
| 12 | Recursion: Mathematics and Python 2027
Автор: Yung-Hsiang Lu
Recursion: Mathematics and Python is designed to help readers develop a clear and systematic understanding of recursion as both a mathematical concept and a programming technique. Rather than presenting recursion as a collection of isolated examples, the book emphasizes recursive thinking: how complex problems can be expressed, analyzed, and solved by breaking them into simpler instances of similar structures. This book is intended for undergraduate students in computer science and computer engineering who already have basic Python programming experience and some prior exposure to recursion. It is well suited for courses in programming, discrete mathematics, data structures, or algorithms. This book can also help instructors seek a resource that tightly integrates mathematical reasoning with executable code. | 826 |
| 13 | Участвуй в КосмоХакатоне 4–6 сентября, решай реальные космические кейсы, поборись за 1,2 млн ₽ и шанс попасть в финал в Москве!
С 4 по 6 сентября в Ростове-на-Дону пройдёт КосмоХакатон Южного и Северо-Кавказского федеральных округов — масштабное соревнование для тех, кто готов превратить данные о нашей планете в реальные технологические решения.
Один хакатон — два формата: участвовать можно очно в Ростове-на-Дону или онлайн из любой точки России. Все команды работают над едиными кейсами, оцениваются по одинаковым критериям и участвуют в общем рейтинге.
В рамках хакатона также пройдёт открытая лекция «Применение космических технологий для решения экологических задач» от Игоря Кожелина, CEO SR Data.
Призовой фонд — 1 200 000₽
Даты проведения: 4–6 сентября
Формат: онлайн и офлайн
Очная площадка: Центр развития предпринимательства «Новый Ростов», ул. Максима Горького, 151, 4 этаж.
🔗 Зарегистрироваться: https://космохакатон.рф | 798 |
| 14 | Agentic GraphRAG_Final.pdf | 910 |
| 15 | Agentic GraphRAG: Integrating Knowledge Graphs, Reasoning, and Agency for Enterprise AI (Final Release) 2026
Автор: Anthony Alcaraz
What if your AI systems could retrieve information, reason over complex knowledge, plan actions, and continuously learn—all while maintaining enterprise-grade security and compliance? Agentic Graph RAG guides technical leaders, engineers, and architects through the next evolution of generative AI. Combining retrieval-augmented generation (RAG) with graph-based reasoning and agentic capabilities, this guide provides a practical blueprint for building scalable, auditable, and intelligent AI systems. | 800 |
| 16 | Building Reliable AI Systems_Final_True.pdf | 942 |
| 17 | Building Reliable AI Systems: Applications and agents you can trust (Final Release) 2026
Автор: Rush Shahani
This book is written for software engineers, machine-learning engineers, AI engineers, and technical leaders who are building or preparing to build LLM-powered applications and agents for production. If you’ve written a prompt, called a model API, or wired up an agentic workflow and felt the distance between a promising demo and an AI system you’d put in front of real users, you are the intended reader.
To follow the examples, you should be comfortable reading Python and have a basic familiarity with machine learning and NLP concepts. You don’t need a research background. Every reliability technique is introduced from the problem it solves, so you can start applying the material without mastering the underlying theory. | 834 |
| 18 | Authorization in Action_Final_True.pdf | 1 001 |
| 19 | Authorization in Action: Build policy-based access control for Zero Trust, APIs, SaaS, and AI agents (Final) 2026
Автор: Phil J. Windley
"Covers every aspect of building dynamic authorization systems. No AI architect should be without it.” - Drummond Reed, Co-author of Self-Sovereign Identity
Underlying all software security is access control: deciding who can get into a system and what they can do once they enter. Authorization in Action shows you how to streamline and automate access control by replacing static manually assigned permissions with a dynamic, Policy-Based Access Control (PBAC) model. Author and identity expert Phillip Windley frames authorization as a first-class citizen in your architecture and shows you how to use the intuitive Cedar policy language to integrate modern access control efficiently into both new and legacy applications. | 912 |
| 20 | Recursion Mathematics and Python.pdf | 884 |
