Форматированное содержание: Введение в .NET; Основы C#; Объективно-ориентированное программирование; Консольные приложения; Продвинутое программирование; Интерфейсы; Массивы, списки, коллекции и словари; Обработка исключительных ситуаций; События; LINQ; Хранение информации; Многопоточность; Добро пожаловать в веб-программирование; Базы данных; Entity framework core; Повторное использование кода; Сетевые сервисы

Форматированное содержание: Design Patterns; Working with Creational Design Patterns; Implementing Structural Design Patterns; Leveraging Behavioral Design Patterns; Architecture and UI Patterns; Exploring Reactive View Library Patterns; Rendering Strategies and Page Hydration; Micro Frontends, Zones, and Islands Architectures; Performance and Security Patterns; Asynchronous Programming Performance Patterns; Event-Driven Programming Patterns; Maximizing Performance - Lazy Loading and Code Splitting; Asset Loading Strategies and Executing Code off the Main Thread

Форматированное содержание: Text Blocks, Locales, Numbers, and Math; Objects, Immutability, Switch Expressions, and Pattern Matching; Working with Date and Time; Records and Record Patterns; Arrays, Collections, and Data Structures; Java I/O: Context-Specific Deserialization Filters; Foreign (Function) Memory API; Sealed and Hidden Classes; Functional Style Programming - Extending APIs; Concurrency - Virtual Threads and Structured Concurrency; Concurrency - Virtual Threads and Structured Concurrency: Diving Deeper; Garbage Collectors and Dynamic CDS Archives; Socket API and Simple Web Server

Форматированное содержание: Getting Started with Unity; Embark on Your Unity Journey; Crafting Scenes and Game Elements; From Blueprint to Reality: Building with Terrain and ProBuilder; Seamless Integration: Importing and Integrating Assets; Mastering Programming and Gameplay Mechanics; Unleashing the Power of C# and Visual Scripting; Dynamic Motion: Implementing Movement and Spawning; Collisions and Health: Detecting Collisions Accurately; Victory or Defeat: Win and Lose Conditions; Starting Your AI Journey: Building Intelligent Enemies for Your Game; Elevating Visuals, Effects, and Audio; Material Alchemy: Using URP and Shader Graph for Stunning Visuals; Captivating Visual Effects: Harnessing Particle Systems and Visual Effect Graph; Enlightening Worlds: Illuminating Scenes with the Universal Render Pipeline; Immersive Realism: Achieving Fullscreen Effects with Post-Processing; Harmonious Soundscapes: Integrating Audio and Music; Designing User Interfaces, Animations and Advanced Concepts; Interface Brilliance: Designing User-Friendly UI; Next-Gen UI: Creating Dynamic Interfaces with UI Toolkit; Animated Realities: Creating Animations with Animator, Cinemachine, and Timeline; Performance Wizardry: Optimizing Your Game with Profiler Tools; From Prototype to Executable: Generating and Debugging Your Game; AR/VR; Massive Worlds: Introduction to DOTS

Форматированное содержание: Introduction to DevOps and role of Python in DevOps; Introducing DevOps Principles; Talking about Python; The Simplest Ways to Start Using DevOps in Python Immediately; Provisioning Resources; Sample Implementations of Python in DevOps; Manipulating Resources; Security and DevSecOps with Python; Automating Tasks; Understanding Event-Driven Architecture; Using Python for CI/CD Pipelines; Let’s Go Further, Let’s Build Bigger; Common DevOps Use Cases in Some of the Biggest Companies in the World; MLOps and DataOps; How Python Integrates with IaC Concepts; The Tools to Take Your DevOps to the Next Level

Форматированное содержание: Теоретические аспекты методов классификации ресурсов по тематическому полю "Экология"; Построение модели тематических словарей для систематизации ресурсов научно-информационного процесса; Прототип информационной системы автоматизированной классификации глаголов по экологии

Форматированное содержание: Приступаем к работе: Введение в язык Python; Выполнение операций; Конструирование инструкций; Определение функций; Импорт модулей; Строки и работа с файлами; Объектное программирование; Обработка запросов; Разработка приложений

Форматированное содержание: Программирование на языке Java; Приступаем к программированию; Базовые типы и основные операторы; Знакомство с классами и объектами; Управляющие инструкции; Массивы; Наследование; Абстрактные классы и интерфейсы; Использование классов и объектов; Обобщенные типы данных; Лямбда-выражения; Обработка исключительных ситуаций; Многопоточное программирование; Приложения с графическим интерфейсом; Обработка событий; Графические компоненты; Меню и панель инструментов; Апплеты; Файлы и аргументы командной строки

Форматированное содержание: О книге и языке C++; Простые программы; Управляющие инструкции; Указатели, массивы и ссылки; Функции; Классы и объекты; Использование классов и объектов; Обобщенные функции и классы; Разные задачи; Математические задачи

Форматированное содержание: An Introduction to Django; Models and Migrations; URL Mapping, Views, and Templates; An Introduction to Django Admin; Serving Static Files; Forms; Advanced Form Validation and Model Forms; Media Serving and File Uploads; Sessions and Authentication; Advanced Django Admin and Customizations; Advanced Templating and Class-Based Views; Building a REST API; Generating CSV, PDF, and Other Binary Files; Testing Your Django Applications; Django Third-Party Libraries; Using a Frontend JavaScript Library with Django

Форматированное содержание: Hello Blazor; Creating Your First Blazor App; Managing State; Understanding Basic Blazor Components; Creating Advanced Blazor Components; Building Forms with Validation; Creating an API; Authentication and Authorization; Sharing Code and Resources; JavaScript Interop; Managing State; Debugging the Code; Testing; Deploy to Production; Moving from, or Combining, an Existing Site; Going Deeper into WebAssembly; Examining Source Generators; Visiting .NET MAUI; Where to Go from Here

Форматированное содержание: Before Pretraining; An Introduction to Pretraining Foundation Models; Dataset Preparation: Part One; Model Preparation; Configure Your Environment; Containers and Accelerators on the Cloud; Distribution Fundamentals; Dataset Preparation: Part Two, the Data Loader; Train Your Model; Finding the Right Hyperparameters; Large-Scale Training on SageMaker; Advanced Training Concepts; Evaluate Your Model; Fine-Tuning and Evaluating; Detecting, Mitigating, and Monitoring Bias; How to Deploy Your Model; Deploy Your Model; Prompt Engineering; MLOps for Vision and Language; Future Trends in Pretraining Foundation Models

Форматированное содержание: Using Python to Simulate a Computer; From Finite State Machines to Computers; High-Speed Introduction to Python; Data Flow in a Computer; Crafting an Interpreter - First Steps; A Little More Python; TC1 Assembler and Simulator Design; Extending the TC1; Simulators for Other Architectures; Using Raspberry Pi to Study a Real Computer Architecture; Raspberry Pi: An Introduction; A Closer Look at the ARM; ARM Addressing Modes; Subroutines and the Stack

Форматированное содержание: Part 1: Getting Started with Natural Language Processing and Networks: Introducing Natural Language Processing; Network Analysis; Useful Python Libraries; Part 2: Graph Construction and Cleanup: NLP and Network Synergy; Even Easier Scraping!; Graph Construction and Cleaning; Part 3: Network Science and Social Network Analysis: Whole Network Analysis; Egocentric Network Analysis; Community Detection; Supervised Machine Learning on Network Data; Unsupervised Machine Learning on Network Data

Форматированное содержание: Part 1: Getting Started with Natural Language Understanding Technology: Natural Language Understanding, Related Technologies, and Natural Language Applications; Identifying Practical Natural Language Understanding Problems; Part 2: Developing and Testing Natural Language Understanding Systems: Approaches to Natural Language Understanding - Rule-Based Systems, Machine Learning, and Deep Learning; Selecting Libraries and Tools for Natural Language Understanding; Natural Language Data - Finding and Preparing Data; Exploring and Visualizing Data; Selecting Approaches and Representing Data; Rule-Based Techniques; Machine Learning Part 1 - Statistical Machine Learning; Machine Learning Part 2 - Neural Networks and Deep Learning Techniques; Machine Learning Part 3 - Transformers and Large Language Models; Applying Unsupervised Learning Approaches; How Well Does It Work? - Evaluation; Part 3: Systems in Action - Applying Natural Language Understanding at Scale: What to Do If the System Isn’t Working; Summary and Looking to the Future

Форматированное содержание: Part 1: Introducing Distributed Tracing: Observability Needs of Modern Applications; Native Monitoring in .NET; The .NET Observability Ecosystem; Low-Level Performance Analysis with Diagnostic Tools; Part 2: Instrumenting .NET Applications: Configuration and Control Plane; Tracing Your Code; Adding Custom Metrics; Writing Structured and Correlated Logs; Part 3: Observability for Common Cloud Scenarios: Best Practices; Tracing Network Calls; Instrumenting Messaging Scenarios; Instrumenting Database Calls; Part 4: Implementing Distributed Tracing in Your Organization: Driving Change; Creating Your Own Conventions; Instrumenting Brownfield Applications

Форматированное содержание: Part 1: Why Metaprogramming?: How Can Metaprogramming Benefit You?; Metaprogramming Concepts; Demystifying through Existing Real-World Examples; Part 2: Leveraging the Runtime: Reasoning about Types Using Reflection; Leveraging Attributes; Dynamic Proxy Generation; Reasoning about Expressions; Building and Executing Expressions; Taking Advantage of the Dynamic Language Runtime; Part 3: Increasing Productivity, Consistency, and Quality: Convention over Configuration; Applying the Open-Closed Principle; Go Beyond Inheritance; Applying Cross-Cutting Concerns; Aspect-Oriented Programming; Part 4: Compiler Magic Using Roslyn: Roslyn Compiler Extensions; Generating Code; Static Code Analysis; Caveats and Final Words

Форматированное содержание: Introduction to Graph Learning; Getting Started with Graph Learning; Graph Theory for Graph Neural Networks; Creating Node Representations with DeepWalk; Fundamentals; Improving Embeddings with Biased Random Walks in Node2Vec; Including Node Features with Vanilla Neural Networks; Introducing Graph Convolutional Networks; Graph Attention Networks; Advanced Techniques; Scaling Up Graph Neural Networks with GraphSAGE; Defining Expressiveness for Graph Classification; Predicting Links with Graph Neural Networks; Generating Graphs Using Graph Neural Networks; Learning from Heterogeneous Graphs; Temporal Graph Neural Networks; Explaining Graph Neural Networks; Applications; Forecasting Traffic Using A3T-GCN; Detecting Anomalies Using Heterogeneous GNNs; Building a Recommender System Using LightGCN; Unlocking the Potential of Graph Neural Networks for Real-World Applications

Форматированное содержание: Networking Primer; Protobuf Primer; Introduction to gRPC; Setting Up a Project; Types of gRPC Endpoints; Designing Effective APIs; Out-of-the-Box Features; More Essential Features; Production-Grade APIs

Форматированное содержание: Приступаем к работе: Введение в язык Python; Выполнение операций; Конструирование инструкций; Определение функций; Импорт модулей; Строки и работа с файлами; Объектное программирование; Обработка запросов; Разработка приложений