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Название: Applications of Deep Machine Learning in Future Energy Systems
Автор: Mohammad-Hassan Khooban
Издательство: Elsevier
Год: 2024
Страниц: 336
Язык: английский
Формат: pdf (true), epub
Размер: 35.8 MB

Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence (AI) techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and operation, before laying out the current AI approaches and our outstanding limitations. Later chapters provide in-depth accounts of specific challenges and the use of innovative third-generation machine learning, including neuromorphic computing, to resolve issues from security to power supply. An essential tool for the management, control, and modelling of future energy systems, Applications of Deep Machine Learning maps a practical path towards AI capable of supporting sustainable energy.

Название: Math for Programming (Early Access)
Автор: Ronald T. Kneusel
Издательство: No Starch Press
Год: 2025
Страниц: 498
Язык: английский
Формат: pdf (true)
Размер: 16.1 MB

A one-stop-shop for all the math you should have learned for your programming career.Math for Programming summarizes all the core math topics a typical professional software engineer needs to know. The book condenses the various mathematics concepts covered in an undergraduate computer science program into a single volume, providing a starting point for independent study or a refresher for those who are some years removed from the classroom. The book first covers preliminary subjects like number representation systems, set theory, and Boolean algebra. Then it dives into the field of discrete mathematics, including functions, induction proofs, number theory, combinatorics, graphs, and trees. The book also examines essential topics in probability, statistics, linear algebra, and calculus. Rather than confine itself to abstract theory, the book focuses on practical application and numerical methods at the level typically encountered by working developers. Hands-on code examples in Python and C also make the topics concrete. Brush up on all the math you should have learned and level-up your career today.

Название: Google JAX Cookbook: Perform Machine Learning and numerical computing with combined capabilities of TensorFlow and NumPy
Автор: Zephyr Quent
Издательство: GitforGits
Год: 2024
Страниц: 333
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

This is the practical, solution-oriented book for every data scientists, Machine Learning engineers, and AI engineers to utilize the most of Google JAX for efficient and advanced Machine Learning. It covers essential tasks, troubleshooting scenarios, and optimization techniques to address common challenges encountered while working with JAX across Machine Learning and numerical computing projects. JAX is a Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale Machine Learning. JAX provides a familiar NumPy-style API for ease of adoption by researchers and engineers. The book starts with the move from NumPy to JAX. It introduces the best ways to speed up computations, handle data types, generate random numbers, and perform in-place operations. It then shows you how to use profiling techniques to monitor computation time and device memory, helping you to optimize training and performance.

Название: First Step to Quantum Computing: A Practical Guide for Beginners
Автор: Javad Shabani, Eva Gurra
Издательство: World Scientific Publishing
Год: 2025
Страниц: 302
Язык: английский
Формат: pdf (true)
Размер: 27.2 MB

Quantum information is a young and evolving field. This compendium introduces quantum information in a comprehensive self-contained guide without assuming a wealth of knowledge prior to reading. The volume highlights intuition on counterintuitive topics such as quantum mechanics, basic mathematical tools and calculations involving linear algebra, and applies these concepts to quantum information with guided problems and coding exercises. Quantum information and quantum computing have evolved into a revolutionary topic where general interest and scientific research have intensified in the recent years. A successful experimental realization of a quantum computer will bring a new technological revolution similar to the advent of the transistor and integrated circuits that form the modern digital world. This applied guide largely benefits mid-level undergraduates and perhaps motivated high schoolers.

Название: Mitigating Bias in Machine Learning
Автор: Carlotta A. Berry, Brandeis Hill Marshall
Издательство: McGraw Hill LLC
Год: 2025
Страниц: 249
Язык: английский
Формат: pdf (true)
Размер: 10.7 MB

This practical guide shows, step by step, how to use Machine Learning to carry out actionable decisions that do not discriminate based on numerous human factors, including ethnicity and gender. The authors examine the many kinds of bias that occur in the field today and provide mitigation strategies that are ready to deploy across a wide range of technologies, applications, and industries. Edited by engineering and computing experts, Mitigating Bias in Machine Learning includes contributions from recognized scholars and professionals working across different artificial intelligence sectors. Each chapter addresses a different topic and real-world case studies are featured throughout that highlight discriminatory machine learning practices and clearly show how they were reduced. This textbook is ideal for undergraduate or graduate students or those seeking an introduction to ML. Since there are few textbooks with practical applications of ML, this contribution will fill in the gap by introducing the topic with an emphasis on a real-world perspective and implementations.

Название: Математика для Data Science. Управляем данными с помощью линейной алгебры, теории вероятностей и статистики
Автор: Томас Нилд
Издательство: Спринт Бук
Год: 2025
Страниц: 352
Язык: русский
Формат: pdf, epub
Размер: 19.6 MB

Освойте математический аппарат, который необходим, чтобы преуспеть в сфере Data Science, машинного обучения и статистики. Автор книги Томас Нилд поможет вам разо­браться в таких дисциплинах, как математический анализ, теория вероятностей, линейная алгебра и статистика, и научиться применять их в контексте таких методов, как линейная регрессия, логистическая регрессия и нейронные сети. Попутно вы узнаете, что представляет собой современная область Data Science и как использовать полученные знания, чтобы достичь максимального успеха в карьере. Чтобы запускать примеры из этой книги, вам нужен только компьютер с любой операционной системой (Windows, macOS или Linux) и любая среда разработки Python 3. Основные библиотеки Python, которые нам понадобятся, — это Numpy, Scipy, Sympy и Sklearn. Если вы не знакомы с Python, то знайте, что это дружелюбный и простой в использовании язык программирования с огромным количеством обучающих материалов.

Название: Facilitating Software Architecture: Empowering Teams to Make Architectural Decisions
Автор: Andrew Harmel-Law
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 570
Язык: английский
Формат: epub
Размер: 10.1 MB

The software architect role is evolving. As systems and their interactions with the teams that build, run, and evolve them become more complex, it's often impossible for those playing the traditional architect roles to be everywhere they need to be. There's simply too much architecture to be done, and the situation has reached a breaking point. There's a better way. Author Andrew Harmel-Law shows you how architects and development teams can collaborate to create and evolve more efficient architectures for their systems. Techniques in this book will help you learn how to create a mindset that allows everyone to practice architecture and build the best systems they've ever experienced. This book is primarily aimed at the two groups I am trying to bring together: developers looking to take steps into architectural accountability and architects learning to add facilitation skills to their repertoire.

Название: Python Programming for Mathematics
Автор: Julien Guillod
Издательство: CRC Press
Серия: The Python Series
Год: 2025
Страниц: 248
Язык: английский
Формат: pdf (true), epub
Размер: 23.0 MB

Python Programming for Mathematics focuses on the practical use of the Python language in a range of different areas of mathematics. Python is a leading programming language in the scientific world. It is perfectly adapted to program mathematical problems. This book focuses on the practical use of the Python language in different areas of mathematics: sequences, linear algebra, integration, graph theory, finding zeros of functions, probability, statistics, differential equations, symbolic calculus, and number theory. Through 55 exercises of increasing difficulty, and corrected in detail, it gives a good overview of the possibilities of using programming in mathematics and to be able to solve complex mathematical problems. It is not necessary to do the exercises in the order suggested, even if some exercises sometimes call upon notions seen in previous exercises. This book does not aim to explain the syntax and principles of the Python language, so the prerequisite is to know the basics. Moreover, the realization of the exercises requires access to a computer or an online service with Python 3.6 (or more recent) completed by the following modules: NumPy, SciPy, SymPy, Matplotlib, Numba, NetworkX, and Pandas.

Название: Advanced Artificial Intelligence, 3rd Edition
Автор: Zhongzhi Shi
Издательство: World Scientific Publishing
Год: 2025
Страниц: 391
Язык: английский
Формат: pdf (true)
Размер: 22.8 MB

This third edition comprehensively captures the cutting-edge research achievements of Artificial Intelligence (AI). Topics are thoroughly revised and updated, presenting the latest techniques and strategies to address the impending challenges facing computer scientists today. Artificial Intelligence is a branch of Computer Science and is a discipline to study machine intelligence that uses artificial methods and techniques, develops intelligent machines or intelligent systems to emulate, extend, and expand human intelligence, and realizes intelligent behavior. Machine Learning is the study of how computers can simulate or implement human learning behavior to acquire new knowledge or skills, and reorganize existing knowledge structures to continuously improve their own performance. Only by allowing computer systems to have human-like learning capabilities can it be possible to achieve human-level Artificial Intelligence. Machine Learning is one of the core issues in AI research and is a very active research field in current AI theoretical research and practical applications. Common Machine Learning methods include inductive learning, analogy learning, analytical learning, reinforcement learning, genetic algorithm, and connection learning. Deep Learning is a new field in Machine Learning research. It imitates the analysis and learning mechanism of human brain neural networks to interpret images, sound, and text data.

Название: Exploring Complex Survey Data Analysis Using R: A Tidy Introduction with {srvyr} and {survey}
Автор: Stephanie Zimmer, Rebecca Powell, Isabella Velásquez
Издательство: CRC Press
Год: 2025
Страниц: 361
Язык: английский
Формат: pdf (true)
Размер: 63.8 MB

Surveys are powerful tools for gathering information, uncovering insights, and facilitating decision-making. However, to ensure the accurate interpretation of results, they require specific analysis methods. In this book, readers embark on an in-depth journey into conducting complex survey analysis with the {srvyr} package and Tidyverse family of functions from the R programming language. Intended for intermediate R users familiar with the basics of the Tidyverse, this book gives readers a deeper understanding of applying appropriate survey analysis techniques using {srvyr}, {survey}, and other related packages. With practical walkthroughs featuring real-world datasets, such as the American National Election Studies and Residential Energy Consumption Survey, readers will develop the skills necessary to perform impactful survey analysis on survey data collected through a randomized sample design. Additionally, this book teaches readers how to interpret and communicate results of survey data effectively. This book is tailored for analysts already familiar with R and the Tidyverse, but who may be new to complex survey analysis in R.