Название: Программирование: введение в профессию (Издание 2,9) (в 3-х томах + Задачи и этюды)
Автор: Столяров А.В.
Издательство: Цетине, Белград
Год: 2025 (изд. 2.9)
Страниц: 225, 226, 227, 164
Язык: русский
Формат: pdf
Размер: 12.6 MB

Первый том серии «Программирование: введение в профессию» включает две основные части. В первую часть книги вошли избранные сведения из истории вычислительной техники, обсуждение некоторых областей математики, непосредственно используемых программистами (таких как алгебра логики, комбинаторика, позиционные системы счисления), математических основ программирования (теория вычислимости и теория алгоритмов), принципы построения и функционирования вычислительных систем, начальные сведения о работе с командной строкой ОС Unix. Вторая часть посвящена начальным навыкам составления компьютерных программ на примере Free Pascal под ОС Unix. Программирование. Введение в профессию. Том 2. Системы и сети. Во второй том вошли части посвящённые языку Си, основным возможностям операционной системы, взаимодействию программ через компьютерные сети, параллельному программированию и внутреннему устройству ядра операционной системы. Программирование. введение в профессию. Том 3 Парадигмы. Третий том посвящён высокоуровневому программированию и возможным подходам к осмыслению программы и её исполнения, известным как «парадигмы программирования». Рассматриваются языки C++, Lisp, Scheme, Prolog, Hope и Tcl.

Название: Automate the Boring Stuff with Python, 3rd Edition (Final Release)
Автор: Al Sweigart
Издательство: No Starch Press
Год: 2025
Страниц: 675
Язык: английский
Формат: True/Retail PDF, True/Retail ePUB
Размер: 45.4 MB

If you’ve ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you? In Automate the Boring Stuff with Python , you’ll learn how to use Python to write programs that do in minutes what would take you hours to do by hand—no prior programming experience required. Once you’ve mastered the basics of programming, you’ll create Python programs that effortlessly perform useful and impressive feats of automation to: –Search for text in a file or across multiple files; –Create, update, move, and rename files and folders; –Search the Web and download online content; –Update and format data in Excel spreadsheets of any size, etc.

Название: Exploring Blazor: Creating Server-side and Client-side Applications in .NET 9, Third Edition
Автор: Taurius Litvinavicius
Издательство: Apress
Год: 2025
Страниц: 181
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Build and develop web applications with Blazor in C#. This new edition not only covers the new structure for the Blazor environment, it also demonstrates the latest features, such as rendering, hosting types, improved security arrangements, and updates the syntax. Two new chapters on Forms and Validation along with Security in Blazor are also added. The code and project layout have been updated in .NET 9 for this new edition. The book starts with an introduction to Blazor, along with its various categories and its basics and syntax, including Razor syntax implementation. You will go through Blazor navigation and life cycle followed by its components. You will then learn features specific to each Blazor type. You will see how Blazor works with storage, files, and jаvascript, and you will create a Blazor code library. You will also create web applications in Blazor using practical implementations and real-life scenarios for both the server side and the client side. After reading this book, you will be able to build web applications with Blazor in C#11 and .NET Core 9.0. For C# and .NET Core developers.

Название: Learning C programming: An Informative and In-depth Guide to C Programming
Автор: Anthony Wallit, Fabio Rumolo
Издательство: Independently published
Серия: How to program with different languages!
Год: October 25, 2022
Страниц: 185
Язык: английский
Формат: epub
Размер: 10.1 MB

New reedited and corrected edition! Do you wish to learn a programming language? C was originally developed for system development tasks, namely for the program that makes up the operating system. C is still in use today. This language was chosen for system development because it generates code that is almost as fast as software written in assembly language, which was previously the standard. C is a simple and basic programming language to learn. This book covers the fundamentals of C, as well as the C Basic Library and current C standards. It is not necessary to have any prior programming expertise. C is a popular programming language that has been popular for decades. C has a wide range of applications. It may be used to code a microprocessor or to create an operating system from the ground up. This book aims to provide a simple and easy-to-understand introduction to the C language. This book aims to be an ultimate guide for keen and interested programmers to be, providing an informative outlook with an in-depth focus in a suitable flow with straightforward communication with organized chapters.

Название: Mathematics for AI: The Hidden Language of Machines
Автор: Gilbert Gutiérrez
Издательство: Independently published
Серия: AI from Scratch: Step-by-Step Guide to Mastering Artificial Intelligence, Book 2
Год: 2025
Страниц: 455
Язык: английский
Формат: epub
Размер: 10.4 MB

Many people dive into AI using pre-built libraries like TensorFlow, PyTorch, and Scikit-Learn, but these tools often act as "black boxes," hiding the mathematical operations that make AI work. Without understanding the underlying math, it’s challenging to fine-tune models, optimize algorithms, and innovate new AI solutions. This book demystifies the math behind AI, helping you go beyond the basics and gain a deeper, more intuitive understanding of how AI truly functions. Artificial Intelligence (AI) is often perceived as a complex, high-tech field that operates through intricate algorithms and deep neural networks. However, beneath this complexity lies a powerful, fundamental force: mathematics. Mathematics is not just a tool for AI; it is the language that defines how machines process, learn from, and understand data. AI algorithms and models rely on mathematical theories and techniques to solve problems, make predictions, and adapt to new information.

Название: Tackling Imbalanced Data with Python: Advanced Techniques and Real-World Applications for Tackling Class Imbalance
Автор: Aarav Joshi
Издательство: 101 Books
Год: 2025
Страниц: 1749
Язык: английский
Формат: epub (true)
Размер: 14.7 MB

Tackling Imbalanced Data with Python: Advanced Techniques and Real-World Applications for Tackling Class Imbalance is a comprehensive guide designed for data scientists, Machine Learning engineers, and practitioners who face the ubiquitous challenge of imbalanced datasets. This book addresses one of the most critical yet underexplored problems in Machine Learning, where traditional algorithms fail to perform effectively on datasets with skewed class distributions. The book provides a systematic approach to understanding and solving class imbalance problems, covering everything from fundamental concepts to cutting-edge techniques. Readers will master data-level solutions including SMOTE and advanced synthetic data generation, algorithm-level approaches such as cost-sensitive learning and focal loss, and ensemble methods specifically designed for imbalanced data. The book extensively covers Deep Learning adaptations, computer vision applications, and natural language processing solutions for imbalanced scenarios. Each chapter includes detailed Python implementations using popular libraries like Scikit-learn, Imbalanced-learn, PyTorch, and TensorFlow.

Название: Python Programming for Young Coders: A Hands-On, Project-Based Introduction to Coding for Beginners, Kids, and Teens
Автор: Anand Pandey
Издательство: Scrib Ink Publishing
Год: 2025
Страниц: 252
Язык: английский
Формат: pdf
Размер: 14.1 MB

Are you a young coder (age 10 +) eager to learn Python? Whether you're a kid, teen, homeschooler, or student—whether in school or college—this book is the perfect starting point for your computer programming journey for beginners. Python Programming for Young Coders breaks down complex programming concepts into easy-to-understand chunks, relating them to real-life examples that resonate with young minds. Starting with the absolute basics, you'll gradually progress through 16 engaging chapters packed with clear explanations, vibrant illustrations, and interactive activities. Each chapter concludes with a review quiz to reinforce learning and ensure mastery of the material. Python is one of the most popular programming languages for beginners. It does not present itself with a complex set of rules and syntax. It has an English-like syntax, which makes it a beginner-friendly language. Python is also a versatile language used for a variety of tasks and in different industries. This book is written keeping beginners in mind. You don’t need to know any programming to get started with this book.

Название: Engineering Mathematics with MATLAB and Simulink
Автор: Farzin Asadi
Издательство: Springer
Год: 2025
Страниц: 496
Язык: английский
Формат: pdf (true)
Размер: 43.1 MB

This book summarizes the mathematics used by engineers, with an emphasis on developing practical skills and techniques for solving mathematical problems in forms typical of engineering. In addition to paper-and-pencil techniques, the book demonstrates how to solve engineering mathematics problems using state-of-the-art software packages. Simulink is a powerful graphical programming environment designed for modeling, simulating, and analyzing dynamical systems. It’s part of the MATLAB suite of tools, offering a user-friendly interface for creating block diagrams that represent system components and their interactions.

Название: Math for Data Science
Автор: Omar Hijab
Издательство: Springer
Год: 2025
Страниц: 588
Язык: английский
Формат: pdf (true)
Размер: 20.8 MB

Math for Data Science presents the mathematical foundations necessary for studying and working in Data Science. The book is suitable for courses in applied mathematics, business analytics, Computer Science, Data Science, and engineering. The text covers the portions of linear algebra, calculus, probability, and statistics prerequisite to Data Science. The highlight of the book is the Machine Learning chapter, where the results of the previous chapters are applied to neural network training and stochastic gradient descent. Also included in this last chapter are advanced topics such as accelerated gradient descent and logistic regression trainability. Clear examples are supported with detailed figures and Python code; Jupyter notebooks and supporting files are available on the author's website. More than 380 exercises and nine detailed appendices covering background elementary material are provided to aid understanding. The standard Python data science packages are used, and a Python index lists the functions used in the text.

Название: Mathematical Foundations Guide to Neural Networks: CNNs, RNNs, LSTMs, Autoencoders, Attention Mechanisms, and More
Автор: Alec Stovari
Издательство: Independently published
Серия: Python Fundamentals
Год: 2025
Страниц: 179
Язык: английский
Формат: pdf
Размер: 10.1 MB

With clear explanations and detailed insights, in 170+ pages, you will learn the inner workings of backpropagation, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs). The book also dives into advanced techniques such as dropout, autoencoders, and attention layers that are transforming the AI landscape. Dive deep into the theory behind each model, understand their applications, and master the mathematics that power modern Machine Learning. Key Topics Covered: - The theoretical foundations of Neural Networks; - Backpropagation and optimization techniques; - Convolutional Neural Networks (CNNs) for image recognition and more; - Recurrent Neural Networks (RNNs) and their sequential data processing power; - Attention mechanisms and transformer models revolutionizing NLP; - Advanced Deep Learning architectures and real-world applications; - Mathematical principles behind Deep Learning algorithms. This book serves as both an academic reference and a practical guide.