Название: Machine Learning and Mechanics Based Soft Computing Applications
Автор: Thi Dieu Linh Nguyen, Joan Lu
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 323
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book highlights recent advances in the area of Machine Learning and robotics-based soft computing applications. The book covers various Artificial Intelligence, Machine Learning, and mechanics, a mix of mechanical computational engineering work. The current computing era has a huge market/potential for Machine Learning, robotics, and soft computing techniques and their applications. With this in view, the book shares latest research and cutting-edge applications useful for professionals and researchers in these areas. This book provides the latest research findings in the emerging technologies with special focus on soft computing intelligent techniques and applications in various fields of engineering. Starting from Artificial Intelligence to mechanics, robotics and how technology is helping in management is covered very selectively. We believe that the collection of these research works will be proved helping to give a support edge to many research problems.

Название: Practical OpenTelemetry: Adopting Open Observability Standards Across Your Organization
Автор: Daniel Gomez Blanco
Издательство: Apress
Год: 2023
Страниц: 236
Язык: английский
Формат: pdf
Размер: 10.08 MB

Learn the value that OpenTelemetry can bring to organizations that aim to implement observability best practices, and gain a deeper understanding of how different building blocks interact with each other to bring out-of-the-box, vendor-neutral instrumentation to your stack. With examples in Java, this book shows how to use OpenTelemetry APIs and configure plugins and SDKs to instrument services and produce valuable telemetry data. You’ll learn how to maximize adoption of OpenTelemetry and encourage the change needed in debugging workflows to reduce cognitive load for engineers troubleshooting production workloads. For each type of signal, that is, baggage, traces, metrics, and logs, this book explores their APIs, SDKs, and best practices needed to instrument applications both manually and automatically via instrumentation libraries. Common use cases for these signals are illustrated with examples in Java, providing short code snippets aimed at explaining individual concepts. To manage context within an application, OpenTelemetry provides a cross-signal Context API to manage key-value pairs. Although this depends on the language, context is not normally handled explicitly, that is, developers don’t need to pass a context object around method invocations. For instance, in Java, it is stored in thread-local storage by default. In this case, the API provides a way to attach, detach, and obtain the context for a current execution.

Название: Numerical Methods with Python: For the Sciences
Автор: William Miles
Издательство: De Gruyter
Год: 2023
Страниц: 328
Язык: английский
Формат: pdf (true)
Размер: 21.0 MB

Introduces students to appropriate use of computer programming within the scientific disciplines using Python. Discusses several common applications of programming and implementation using real world examples and hands on programming exercises. Students learn how to model situations such as image recognition, medical diagnosis, spread of disease, and others. In order to present the techniques and methodologies, we use the Python programming language. Thus, in addition to learning the numerical methods, students will also learn how to program using Python. It is a powerful language that is available to everyone at no cost (since it is open-sourced). The text begins by discussing some of the fundamental tasks that we must be able to accomplish using the programming language.

Название: Software Usability Updates
Автор: Laura M. Castro
Издательство: ITexLi
Год: 2023
Страниц: 103
Язык: английский
Формат: pdf (true)
Размер: 10.7 MB

This volume is a collection of high-quality contributions for developers and non-developers alike. Beyond the preliminaries, the book is organized into two other parts: “Designing for Usability” and “Testing for Usability”. The chapters in the second section, “Designing for Usability”, offer valuable insights and practical guidance to take into account during the early stages of product conception and development. On the other hand, the chapters in the third section, “Testing for Usability”, reflect and formalize software usability’s evaluation and validation processes. These two complementary views on the subject make this book a balanced and comprehensive volume, which the reader will undoubtedly find both interesting and useful.

Название: Machine Learning: Multi-Agent Technologies
Автор: Igor Sheremet, Andries Engelbrecht
Издательство: ITexLi
Год: 2023
Страниц: 109
Язык: английский
Формат: pdf (true)
Размер: 15.2 MB

Multi-agent systems (MASs) are defined as a group of interacting entities or agents sharing a common environment that changes over time, with capabilities of perception and action, and the mechanisms for their coordination provide a modern perspective on systems that traditionally were regarded as centralized. The main characteristics of agents are learning and adaptation. In the last few years, MASs have received tremendous attention from scholars in different fields. However, there are still challenges faced by MASs and their integration with Machine Learning (ML) methods. The primary goal of the study is to provide a broad review of the current developments in the field of MASs combined with ML methods. Machine Learning (ML) is a subset of Artificial Intelligence (AI) that concerns the development of algorithms, which allows the machine to learn via inductive inference based on observation data that represent incomplete information about statistical phenomena. To carry out the learning process an algorithm is used based on examples of the task we want to solve (data) and letting the computer find patterns and make inferences that optimize the decision-making according to a user-defined objective. Based on the training strategy, ML can be divided into three classical categories with different learning approaches: supervised learning, unsupervised learning, and reinforcement learning.

Название: Artificial Intelligence for Cognitive Modeling: Theory and Practice
Автор: Pijush Dutta, Souvik Pal, Asok Kumar
Издательство: CRC Press
Год: 2023
Страниц: 295
Язык: английский
Формат: pdf (true)
Размер: 26.6 MB

This book is written in a clear and thorough way to cover both the traditional and modern uses of Artificial Intelligence (AI) and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model. This book contains 15 chapters altogether. This book is unique for its contents, clarity, precision of presentation, and the overall completeness of its chapters. All the simulation results are obtained from the MATLAB code and SIMULINK.

Название: The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions
Автор: Marco Scutari, Mauro Malvestio
Издательство: CRC Press
Серия: Machine Learning & Pattern Recognition
Год: 2023
Страниц: 357
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Machine Learning (ML) has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life. The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions discusses how modern software engineering practices are part of this revolution both conceptually and in practical applictions. Comprising a broad overview of how to design Machine Learning pipelines as well as the state-of-the-art tools we use to make them, this book provides a multi-disciplinary view of how traditional software engineering can be adapted to and integrated with the workflows of domain experts and probabilistic models. The book starts with a brief introduction to Machine Learning and software engineering, to set out how we view them and how we think that they should interact in practical applications. The remainder is structured in four parts, from foundational to practical.

Название: Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning, 2nd Edition (Fifth Early Release)
Автор: Kyle Gallatin, Chris Albon
Издательство: O’Reilly Media, Inc.
Год: 2023-03-01
Страниц: 253
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.2 MB

This practical guide provides more than 200 self-contained recipes to help you solve Machine Learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including Pandas and Scikit-learn, you'll be able to address specific problems all the way from loading data to training models and leveraging neural networks. Each recipe in this updated edition includes code that you can copy, paste, and run with a toy dataset to ensure it works. From there, you can adapt these recipes according to your use case or application. Recipes include a discussion that explains the solution and provides meaningful context. Go beyond theory and concepts by learning the nuts and bolts you need to construct working Machine Learning applications. NumPy is a foundational tool of the Python Machine Learning stack. NumPy allows for efficient operations on the data structures often used in Machine Learning: vectors, matrices, and tensors.

Название: C# Programming & Software Development: 6 In 1 Coding Syntax, Expressions, Interfaces, Generics And App Debugging
Автор: Richie Miller
Издательство: Pastor Publishing Ltd
Год: 2023
Страниц: 819
Язык: английский
Формат: pdf, epub
Размер: 35.5 MB

If you want to discover how to become a software developer using C#, this book is for you! Maybe you're a developer somewhere on the spectrum from newbie to veteran or maybe you're not a programmer at all, but you do have at least a conversational understanding of basic programming concepts, like branching, loops and functions, and at least a basic idea of what classes are about. Since you're reading this book, I assume you're curious to know more about C#, but not necessarily because you need to become a C# practitioner. I'm also going to assume you're skeptical in the most complimentary sense. Part of what makes developers good developers is a healthy resistance to taking bold statements about a programming language's benefits at face value. So I will avoid making bold statements about C#'s benefits without illustrating the point or showing you how you can convince yourself. Lastly, I assume you either aspire to be a C# developer or perhaps just someone who can communicate more effectively with C# developers. And so at this point, I just want to understand the essence of what makes C# tick as opposed to spending a lot of time in the details. With all of that in mind, this book is less about the syntax of C# and more about the reasons why bothering to learn its syntax might be useful to you. The goal with this book is to kick start your discovery of C# by taking the following approach.

Название: 40 алгоритмов, которые должен знать каждый программист на Python
Автор: Ахмад Имран
Издательство: Питер
Год: 2023
Формат: pdf
Страниц: 368
Размер: 12,4 Мб
Язык: русский

Понимание работы алгоритмов и умение применять их для решения прикладных задач – must-have для любого программиста или разработчика. Эта книга поможет вам не только развить навыки использования алгоритмов, но и разобраться в принципах их функционирования, в их логике и математике. Вы начнете с введения в алгоритмы, от поиска и сортировки перейдете к линейному программированию, ранжированию страниц и графам и даже поработаете с алгоритмами машинного обучения. Теории не бывает без практики, поэтому вы займетесь прогнозами погоды, кластеризацией твитов, механизмами рекомендаций фильмов. И, наконец, освоите параллельную обработку, что даст вам возможность решать задачи, требующие большого объема вычислений. Дойдя до конца, вы превратитесь в эксперта по решению реальных вычислительных задач с применением широкого спектра разнообразных алгоритмов.