Название: Banach Space Valued Neural Network
Автор: George A. Anastassiou
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 429
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book is about the generalization and modernization of approximation by neural network operators. Functions under approximation and the neural networks are Banach space valued. These are induced by a great variety of activation functions deriving from the arctangent, algebraic, Gudermannian, and generalized symmetric sigmoid functions. Ordinary, fractional, fuzzy, and stochastic approximations are exhibited at the univariate, fractional, and multivariate levels. Iterated-sequential approximations are also covered. The book’s results are expected to find applications in the many areas of applied mathematics, Computer Science and engineering, especially in Artificial Intelligence (AI) and Machine Learning (ML).

Название: New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics
Автор: Oscar Castillo, Patricia Melin
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2022
Страниц: 471
Язык: английский
Формат: pdf (true), epub
Размер: 56.9 MB

In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.

Название: Recent Innovations in Artificial Intelligence and Smart Applications
Автор: Mostafa Al-Emran, Khaled Shaalan
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2022
Страниц: 387
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book tackles the recent research trends on the role of AI in advancing automotive manufacturing, augmented reality, sustainable development in smart cities, telemedicine, and robotics. It sheds light on the recent AI innovations in classical Machine Learning, Deep Learning, Internet of Things (IoT), Blockchain, knowledge representation, knowledge management, Big data, and natural language processing (NLP). The edited book covers empirical and reviews studies that primarily concentrate on the aforementioned issues, which would assist scholars in pursuing future research in the domain and identifying the possible future developments of AI applications. The rapid emergence of Deep Learning (DL) algorithms has paved the way for bringing Artificial Intelligence (AI) services to end users. The intersection between edge computing and AI has brought an exciting area of research called edge artificial intelligence (Edge AI).

Название: Advances in Swarm Intelligence: Variations and Adaptations for Optimization Problems
Автор: Anupam Biswas, Can B. Kalayci, Seyedali Mirjalili
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 416
Язык: английский
Формат: pdf (true)
Размер: 10.15 MB

Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines science and technology. This book emphasizes the studies of existing SI techniques, their variants and applications. The book also contains reviews of new developments in SI techniques and hybridizations. Algorithm specific studies covering basic introduction and analysis of key components of these algorithms, such as convergence, balance of solution accuracy, computational costs, tuning and control of parameters. Application specific studies incorporating the ways of designing objective functions, solution representation and constraint handling. The book also includes studies on application domain specific adaptations in the SI techniques. Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines in both science and technology. Generally speaking, the algorithms that come under SI domain are typically population-based meta-heuristics techniques and are mostly inspired by nature. This book strives to cover all the major SI techniques, including particle swarm optimization, ant colony optimization, firefly algorithm, dragonfly algorithm, cuckoo search, and many more.

Название: Data Visualization with Python and jаvascript, 2nd Edition
Автор: Kyran Dale
Издательство: O’Reilly Media
Год: 2022-10-04: Ninth Release
Формат: ePUB
Страниц: 550
Размер: 25,4 Mb
Язык: English

How do you turn raw, unprocessed, or malformed data into dynamic, interactive web visualizations? In this practical book, author Kyran Dale shows data scientists and analysts–as well as Python and jаvascript developers–how to create the ideal toolchain for the job. By providing engaging examples and stressing hard-earned best practices, this guide teaches you how to leverage the power of best-of-breed Python and jаvascript libraries.

Название: Programming in Two Semesters: Using Python and Java
Автор: Quentin Charatan, Aaron Kans
Издательство: Springer
Год: 2022
Формат: True PDF
Страниц: 665
Размер: 29,8 Mb
Язык: English

This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts.

Название: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition
Автор: Aurelien Geron
Издательство: O’Reilly Media
Год: 2022
Формат: ePUB
Страниц: 751
Размер: 27,3 Mb
Язык: English

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

Название: Functional and Concurrent Programming: Core Concepts and Features
Автор: Michel Charpentier
Издательство: Pearson
Год: 2022
Формат: PDF
Страниц: 630
Размер: 10 Mb
Язык: English

The functional and concurrent programming language features supported by modern languages can be challenging, even for experienced developers. These features may appear intimidating to OOP programmers because of a misunderstanding of how they work. Programmers first need to become familiar with the abstract concepts that underlie these powerful features.

Название: Tree-Based Methods for Statistical Learning in R: A Practical Introduction with Applications in R
Автор: Brandon M. Greenwell
Издательство: CRC Press
Год: 2022
Страниц: 405
Язык: английский
Формат: pdf (true)
Размер: 29.1 MB

Tree-based Methods for Statistical Learning in R provides a thorough introduction to both individual decision tree algorithms (Part I) and ensembles thereof (Part II). Part I of the book brings several different tree algorithms into focus, both conventional and contemporary. Building a strong foundation for how individual decision trees work will help readers better understand tree-based ensembles at a deeper level, which lie at the cutting edge of modern statistical and Machine Learning (ML) methodology. The book follows up most ideas and mathematical concepts with code-based examples in the R statistical language; with an emphasis on using as few external packages as possible. For example, users will be exposed to writing their own random forest and gradient tree boosting functions using simple for loops and basic tree fitting software (like rpart and party/partykit), and more. The core chapters also end with a detailed section on relevant software in both R and other opensource alternatives (e.g., Python, Spark, and Julia), and example usage on real data sets. While the book mostly uses R, it is meant to be equally accessible and useful to non-R programmers.

Название: Time Series for Data Science: Analysis and Forecasting
Автор: Wayne A. Woodward, Bivin P. Sadler, Stephen D. Robertson
Издательство: CRC Press
Год: 2022
Страниц: 529
Язык: английский
Формат: pdf (true), epub
Размер: 63.8 MB

Data Science students and practitioners want to find a forecast that “works” and don’t want to be constrained to a single forecasting strategy, Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble modelling for combining information from several strategies. Covering time series regression models, exponential smoothing, Holt-Winters forecasting, and Neural Networks. It places a particular emphasis on classical ARMA and ARIMA models that is often lacking from other textbooks on the subject. For software choice, we have created an R package tswge, which is available on CRAN to accompany this book. Because of the clearly described R syntax, students should not be required to have previous knowledge of R. The number of examples and the focus on participation by the reader to enter the provided R code will ground the students with the necessary R coding skills. In fact, this textbook could be a resource for an introductory course in R programming with time series applications.