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Название: Machine Learning for Complex and Unmanned Systems
Автор: Jose Martinez-Carranza, Everardo Inzunza-González, Enrique Efrén García-Guerrero
Издательство: CRC Press
Год: 2024
Страниц: 386
Язык: английский
Формат: pdf (true)
Размер: 25.4 MB

This book highlights applications that include Machine Learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects Machine Learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of Machine Learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems, in the areas of Artificial Intelligence (AI), cryptography, embedded hardware, electronics, the Internet of Things (IoT), and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research.

Название: Online Machine Learning: A Practical Guide with Examples in Python
Автор: Eva Bartz, Thomas Bartz-Beielstein
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2024
Страниц: 163
Язык: английский
Формат: pdf (true), epub
Размер: 19.0 MB

This book deals with the exciting, seminal topic of Online Machine Learning (OML). The content is divided into three parts: the first part looks in detail at the theoretical foundations of OML, comparing it to Batch Machine Learning (BML) and discussing what criteria should be developed for a meaningful comparison. The second part provides practical considerations, and the third part substantiates them with concrete practical applications. The book is equally suitable as a reference manual for experts dealing with OML, as a textbook for beginners who want to deal with OML, and as a scientific publication for scientists dealing with OML since it reflects the latest state of research. But it can also serve as quasi OML consulting since decision-makers and practitioners can use the explanations to tailor OML to their needs and use it for their application and ask whether the benefits of OML might outweigh the costs. Chapter 1 describes the motivation for this book and the objective. Chapter 2 gives an overview and evaluation of methods and algorithms with special focus on supervised learning. Chapter 3 describes procedures for drift detection. Updateability of OML procedures is discussed in Chap. 4. Chapter 5 explains procedures for the evaluation of OML methods. Chapter 6 deals with special requirements for OML. Possible OML applications are presented in Chap. 7 and evaluated by experts in official statistics. The availability of the algorithms in software packages, especially for R and Python, is presented in Chap. 8.

Название: Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas and Scikit-Learn
Автор: Abdelaziz Testas
Издательство: Apress
Год: 2023
Страниц: 500
Язык: английский
Формат: pdf (true), epub (true), mobi
Размер: 10.1 MB

Migrate from Pandas and Scikit-learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and Machine Learning with PySpark. You will learn to translate Python code from Pandas/Scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular Machine Learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Naive Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using PySpark, the industry standard for building scalable ML data pipelines. Data scientists, data engineers, and machine learning practitioners who have some familiarity with Python, but who are new to distributed machine learning and the PySpark framework.

Название: Exploring University Mathematics with Python
Автор: Siri Chongchitnan
Издательство: Springer
Год: 2023
Страниц: 521
Язык: английский
Формат: pdf (true)
Размер: 23.7 MB

This book provides a unique tour of university mathematics with the help of Python. A typical mathematics university curriculum would include some element of programming, usually in a standalone module. However, in my experience teaching at several UK universities, students often regard programming as just another module that is disparate from a typical ‘pen-and-paper’ module. In my opinion, this is an extremely unhealthy viewpoint, because programming can often help us gain a more solid understanding of mathematics in comparison to a purely pen-and-paper approach. It is true that much of university mathematics is driven by theorems and proofs, and it is also true that Python does not prove theorems. However, Python gives us the power and freedom to glimpse into the unknown, leading us towards insightful conjectures that would have been difficult to formulate otherwise. Hence, I was motivated to write a mathematics textbook that is richly interwoven with Python, rather than another Python textbook with some mathematical examples. The spirit of this book is one of mathematical exploration and investigation. I want to show students that Python can hugely enrich our understanding of mathematics through.

Название: Python – это просто. Пошаговое руководство по программированию и анализу данных
Автор: Нилаб Нисчал
Издательство: БХВ
Год: 2023
Формат: pdf
Размер: 120 Мб
Качество: Хорошее
Язык: Русский

Рассмотрены основы синтаксиса языка Python на примере дистрибутива Anaconda. Показаны приложения IPython, Spyder IDE, Jupyter Notebook. Описан синтаксис переменных, функций, циклов. Подробно изучаются структуры данных в Python: строки, списки, кортежи, множества и словари. Объясняется понятие классов и их применение в объектно-ориентированном программировании. Описаны возможности библиотеки обработки изображений Pillow, библиотеки Tkinter для создания приложений с графическим интерфейсом.

Название: Advances on Mathematical Modeling and Optimization with Its Applications
Автор: Gunjan Mukherjee, Biswadip Basu Mallik, Rahul Kar
Издательство: CRC Press
Серия: Emerging Technologies
Год: 2024
Страниц: 279
Язык: английский
Формат: pdf (true)
Размер: 22.2 MB

Advances on Mathematical Modeling and Optimization with Its Applications discusses optimization, equality, and inequality constraints and their application in the versatile optimizing domain. It further covers non-linear optimization methods such as global optimization, and gradient-based non-linear optimization, and their applications. Math has become a part of our everyday life. From the minute we wake up to the moment we go to bed, we use mathematics in every aspect of our lives. The exhaustive contribution of mathematical aspects and applicative knowledge has become research worthy due to the invention and discoveries of many advanced sorts of theorems, Whether a person is Data Scientist, Data Analyst, or Machine Learning Engineer, “Mathematics” should be a key focus of the studies. Artificial Intelligence (AI) and Machine Learning (ML) are hot topics in the computer world, and for good reason. They help companies streamline operations and unearth data so that they can make better business decisions. The business growth is directly or indirectly managed by the proper trend analysis and the predictive approach of growth to the ultimate level of development. They’re boosting almost every industry by allowing employees to work more effectively, and they’re fast becoming a critical piece of technology for businesses to remain competitive with others. Python is the most popular computer program for applying mathematical and statistical methods to AI development and applications. Therefore, we have demonstrated the applications of Python in different applications of mathematics in AI in this book.

Название: Advanced Data Fetching Patterns in React : Fast, User-Friendly Data Fetching for Developers
Автор: Juntao Qiu
Издательство: Leanpub
Год: 2024-01-27
Страниц: 105
Язык: английский
Формат: pdf (true), epub
Размер: 22.3 MB

"Advanced Data Fetching Patterns in React" is your essential guide to mastering the art of efficient data fetching in React. Discover innovative strategies and the latest features to elevate your React applications, transforming them into models of performance and efficiency. Dive in and reshape the way you handle data in your React projects! If you're developing React applications with rich API integrations, you might have noticed a trend: the more complex your app becomes, the slower and more cumbersome it feels. React's ecosystem is continually evolving, introducing many new concepts and techniques. Terms like React Server Components, Server-Side Rendering (SSR), and the Suspense API are not mere buzzwords; they represent significant shifts in how we approach building and optimizing React applications. However, mastering these advanced concepts can seem daunting. This book is your guide through the complexities of modern React development. We'll journey through the intricacies of parallel requests, lazy loading, and SSR and delve into the innovative territories of Server Components and the Suspense API. Each topic is broken down into understandable segments, providing actionable insights and clear explanations.

Название: Model-Driven Software Systems Development Using the Meta-Artifact Process
Автор: Wayne O’Brien
Издательство: CRC Press
Год: 2024
Страниц: 145
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The importance of architecture for software systems is widely accepted, but the role of architecture in the overall development process is not so clear. Presenting an architecture-centric process, Model-Driven Software Systems Development Using the Meta-Artifact Process makes the role of architecture clear. At its core, this book is about developing software systems and, more specifically, software code. It describes three major innovations for making software, which are combined with five widely used enabling technologies, to provide a complete, hypothesis-driven software development process known as Meta-Artifact Process (MAP). Having complete requirements is essential for making good software and supports the hypothesis-driven MAP. Model-​Driven Software Systems Development Using the Meta-​Artifact Process, a guide for making software (MSW) can be used for large or small systems, using agile methods wherever appropriate, while supporting the OMG Essence standard, and working within an overarching architecture. MSW is concerned in particular with software systems, specifically software codes. Unless specified otherwise, the words system or software or program or code refer to this software code. In some references to hypotheses, program is used as including all aspects of a software system, such as its architecture. MSW works in conjunction with an organization’s existing processes, especially Model-​Driven Development (MDD). Some familiarity with MDD is useful but not essential to understand the ideas.

Название: Clean Code: An Agile Guide to Software Craft
Автор: Frahaan Hussain, Kameron Hussain
Издательство: Sonar Publishing
Год: October 17, 2023
Страниц: 335
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Clean Code: An Agile Guide to Software Craft is an indispensable resource for software developers and engineers striving to write clean, maintainable, and efficient code. Authored by Robert C. Martin, a renowned expert in software development, this book delves deep into the art and science of writing code that is not only functional but also easy to read and understand. In this comprehensive guide, Martin introduces you to the principles and practices of clean code, emphasizing the importance of writing code that communicates its intent clearly. He presents a set of practical guidelines and techniques for improving the quality of your codebase, making it easier to maintain and extend in the long run. You'll learn how to spot and rectify common code smells, design clean and intuitive functions and classes, and refactor existing code to align with best practices. Throughout the book, real-world examples and case studies illustrate the transformation of messy, convoluted code into elegant and clean solutions. Martin discusses the significance of meaningful variable names, proper code formatting, and effective commenting to enhance code clarity. Additionally, you'll explore topics such as testing, error handling, and code organization, all geared toward producing code that stands the test of time.

Название: Wavelets in Soft Computing, Second Edition
Автор: Marc Thuillard
Издательство: World Scientific Publishing
Серия: World Scientific Series in Robotics and Intelligent Systems
Год: 2023
Страниц: 320
Язык: английский
Формат: pdf (true), epub
Размер: 38.0 MB

The comprehensive compendium furnishes a quick and efficient entry point to many multiresolution techniques and facilitates the transition from an idea into a real project. It focuses on methods combining several soft computing techniques (fuzzy logic, neural networks, genetic algorithms) in a multiresolution framework. Illustrated with numerous vivid examples, this useful volume gives the reader the necessary theoretical background to decide which methods suit his/her needs. New materials and applications for multiresolution analysis are added, including notable research topics such as Deep Learning, graphs, and network analysis. Many Deep Learning applications incorporate a wavelet decomposition stage to better capture features at different resolutions, a quite sensible step as the size of an object in an image may greatly vary. A fascinating aspect that we discuss in a new chapter is that multiresolution is at the heart of the functioning of Deep Learning. Neural networks on graphs are important in studying communication networks and analyzing internet data. Here also, multiresolution permits a better analysis. The research community has broadly integrated the idea that the integration of multiresolution often improves algorithms. This new edition aims to capture some of these exciting new developments. Readership: Researchers, professionals, academics and graduate students in fuzzy logic.