Название: Clean Architecture for Android: Implement Expert-led Design Patterns to Build Scalable, Maintainable, and Testable Android Apps
Автор: Eran Boudjnah
Издательство: BPB Publications
Год: 2023
Страниц: 397
Язык: английский
Формат: epub (true)
Размер: 10.2 MB

Architect an Android application independent of UI, databases and frameworks. "Clean Architecture for Android" was written to help developers apply Clean Architecture to their projects. The book will explain why Clean Architecture is so valuable. It will demonstrate how you can use this architecture to build more reliable and extensible apps. It will also show you how Clean Architecture helps ensure your projects are easy to maintain. This book will explain the structure and functions at each level of the architecture. It will show you how to integrate Clean Architecture into your project and gradually transition from your current architecture to the new one. Finally, it will demonstrate how to apply the various Clean Architecture concepts by practicing and demonstrating their value. If you are new to creating Android apps, this book will give you the foundational knowledge you need to start creating apps using Clean Architecture.

Название: Edge Computing with Python: End-to-end Edge Applications, Python Tools and Techniques, Edge Architectures, and AI Benefits
Автор: Abhinandan Bhadauria
Издательство: BPB Publications
Год: 2023
Страниц: 462
Язык: английский
Формат: epub (true)
Размер: 10.6 MB

Deep Dive into Edge Computing and its Implementations. In this book, readers will learn what Edge Computing is, what its possible applications are, and how advantageous it is. This book provides thorough instructions for using Python to build every potential edge application. The book begins by configuring the programming environment with tools like VS Code, Python, and several popular libraries like SciPy, NumPy, and Pandas. Then, the book explains gaining access to IO devices, data handling, data storage, cloud connectivity, and hosting ready and pre-trained machine learning models step by step. The book delves into sophisticated ideas such as Docker Containers, MQTT, and FIWARE and how one can use them to construct Edge applications. In addition, the book details the Siemens Edge computing platform and how to use it for rapidly developing Edge applications. After reading this book, knowledge of Edge Computing's architecture, its benefits, and drawbacks will give readers a competitive advantage in the market.

Название: Graph Learning and Network Science for Natural Language Processing
Автор: Muskan Garg, Amit Kumar Gupta, Rajesh Prasad
Издательство: CRC Press
Год: 2023
Страниц: 272
Язык: английский
Формат: pdf (true)
Размер: 11.25 MB

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Computers are machines, and cannot understand the free-flowing language used by humans for communication. They understand the language of 0s and 1s, which is a machine language called binary language. Without processing natural language, it’s difficult for humans to talk to computers. For this reason, an artificial intelligence-based solution called natural language processing (NLP) has been developed. NLP techniques help computers to interpret, understand and manipulate human language. This book is aimed at researchers and graduate students in Computer Science, natural language processing, and Deep and Machine Learning.

Название: Convergence of Deep Learning in Cyber-IoT Systems and Security
Автор: Rajdeep Chakraborty, Anupam Ghosh, Jyotsna Kumar Mandal
Издательство: Wiley-Scrivener
Серия: Artificial Intelligence and Soft Computing for Industrial Transformation
Год: 2023
Страниц: 472
Язык: английский
Формат: pdf (true)
Размер: 50.5 MB

Deep Learning (also known as deep structured learning) is part of a broader family of Machine Learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi- supervised or unsupervised. Deep Learning architectures such as deep neural networks, deep belief networks, deep reinforcement learning, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing (NLP), machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Artificial neural networks (ANNs) were inspired by information processing and distributed communication nodes in biological systems. ANNs have various differences from biological brains. Deep Learning approaches are now used in every aspect of cyber systems and IoT systems. The main goal of this book is to bring to the fore unconventional cryptographic methods to provide cyber security, including cyber-physical system security and IoT security through Deep Learning techniques and analytics with the study of all these systems.

Название: Modern Typescript
Автор: Ben Beattie-Hood
Издательство: Leanpub
Год: 2021-12-23
Страниц: 104
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Covering from basic building of interfaces to advanced use of unions, partials, intersections, and mapped types. Join me for this deep-dive from fundamentals to advanced aspects of Typescript, and how you can leverage its static testing system to accelerate your development velocity. For newcomers and advanced users, this deep-dive covers the fundamentals as well as a huge range of the advanced aspects of Typescript, and how you can leverage its static testing system to accelerate your development velocity. The last and only book you'll need to learn Typescript inside out.

Название: Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems
Автор: Om Prakash Jena, Bharat Bhushan, Nitin Rakesh
Издательство: CRC Press
Год: 2022
Страниц: 397
Язык: английский
Формат: pdf (true)
Размер: 27.4 MB

Rapid population growth coupled with the evolution of numerous diseases is a matter of concern worldwide. Due to this, the healthcare industry has emerged as an essential service sector. The generation of a large amount of healthcare data and the lack of insight from that data are significant problems in the healthcare sector. Therefore, there is a need for a fully effective and automated system that can help medical stakeholders to take prompt action at the right time. Artificial intelligence (AI) and machine learning (ML) have a very long association with the healthcare sector dating back to 1980s. It gained momentum with the emergence of rule-based systems, hierarchical clustering, and various regression models. ML is an important utility of AI that provides systems with the capacity to automatically examine and enhance action without being specially programmed. However, neither the computers nor the algorithms were efficient enough to enable effective ML based systems. The last five years had seen tremendous rise in the adoption of ML techniques mainly due to emergence of neural network that enhanced the overall computational power. Deep Learning (DL) is a subset of ML where innovations have led to the construction of several novel deep neural network architectures that can be used for the classification of large data sets. AI, ML, and DL techniques can be employed for efficient knowledge discovery from healthcare data.

Название: Hybrid Quantum Metaheuristics: Theory and Applications
Автор: Siddhartha Bhattacharyya, Mario Koppen, Elizabeth Behrman, Ivan Cruz-Aceves
Издательство: CRC Press
Серия: Quantum Machine Intelligence
Год: 2022
Страниц: 276
Язык: английский
Формат: pdf (true)
Размер: 15.3 MB

A metaheuristic is a heuristic (partial search) algorithm that is more or less an efficient optimization algorithm to real-world problems. Hybrid metaheuristics refer to a proper and judicious combination of several other metaheuristics and Machine Learning algorithms. The hybrid metaheuristics have been found to be more robust and failsafe owing to the complementary character of the individual metaheuristics in the resultant combination. This is primarily due to the fact that the vision of hybridization is to combine different metaheuristics such that each of the combination supplements the other in order to achieve the desired performance. Typical examples use fuzzy-evolutionary, neuro-evolutionary, neuro-fuzzy evolutionary, rough-evolutionary approaches to name a few. Recently, chaos theory has also found wide applications in evolving efficient hybrid metaheuristics. Quantum computer, as the name suggests, principally works on several quantum physical features. These could be used as an immense alternative to today’s apposite computers since they possess faster processing capability (even exponentially) than classical computers. The term quantum computing stems from the synergistic combination of quantum mechanical principles and classical information theory conjoined with principles of Computer Science.

Название: Modern Applied Regressions: Bayesian and Frequentist Analysis of Categorical and Limited Response Variables with R and Stan
Автор: Jun Xu
Издательство: CRC Press
Год: 2023
Страниц: 298
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Modern Applied Regressions creates an intricate and colorful mural with mosaics of categorical and limited response variable (CLRV) models using both Bayesian and Frequentist approaches. Written for graduate students, junior researchers, and quantitative analysts in behavioral, health, and social sciences, this text provides details for doing Bayesian and frequentist data analysis of CLRV models. Each chapter can be read and studied separately with R coding snippets and template interpretation for easy replication. Along with the doing part, the text provides basic and accessible statistical theories behind these models and uses a narrative style to recount their origins and evolution. We use R as the statistical analysis environment exclusively for all the models discussed in this text, accompanied with discussions about other software applications for Bayesian analysis. R is an open-source free software for statistical analysis, and it is a member of the GNU Project that advocates users’ freedom to create, extend, and use the software.

Название: Modern Adaptive Fuzzy Control Systems
Автор: Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang
Издательство: Springer
Год: 2023
Страниц: 161
Язык: английский
Формат: pdf (true)
Размер: 10.3 MB

This book explains the basic concepts, theory and applications of fuzzy systems in control in a simple unified approach with clear ex-amples and simulations in the MATLAB programming language. Fuzzy systems, especially, type-2 neuro-fuzzy systems, are now used extensively in various engineering fields for different purposes. In plain language, this book aims to practically explain fuzzy sys-tems and different methods of training and optimizing these systems. For this purpose, type-2 neuro-fuzzy systems are first analyzed along with various methods of training and optimizing these systems through implementation in MATLAB. These systems are then em-ployed to design adaptive fuzzy controllers. The authors aim at pre-senting all the well-known optimization methods clearly and code them in the MATLAB language.

Название: Bayesian Reasoning and Gaussian Processes for Machine Learning Applications
Автор: Hemachandran K., Shubham Tayal
Издательство: CRC Press
Год: 2022
Страниц: 149
Язык: английский
Формат: pdf (true)
Размер: 10.9 MB

This book introduces Bayesian reasoning and Gaussian processes into Machine Learning applications. Bayesian methods are applied in many areas, such as game development, decision making, and drug discovery. It is very effective for Machine Learning algorithms in handling missing data and extracting information from small datasets.Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning, which is followed by Gaussian process introduction, classification, regression, covariance, and performance analysis of Gaussian processes with other models. This book is aimed at graduates, researchers, and professionals in the field of Data Science and Machine Learning.