Название: Graph Neural Networks in Action (MEAP v4)
Автор: Keita Broadwater
Издательство: Manning Publications
Год: 2022
Страниц: 197
Язык: английский
Формат: pdf, epub
Размер: 15.1 MB

A hands-on guide to powerful graph-based Deep Learning models! Learn how to build cutting-edge graph neural networks (GNN) for recommendation engines, molecular modeling, and more. Graph Neural Networks in Action teaches you to create powerful deep learning models for working with graph data. You’ll learn how to both design and train your models, and how to develop them into practical applications you can deploy to production. Go hands-on and explore relevant real-world projects as you dive into graph neural networks perfect for node prediction, link prediction, and graph classification. Inside this practical guide, you’ll explore common graph neural network architectures and cutting-edge libraries, all clearly illustrated with well-annotated Python code. If you are an intermediate user of Python, and have some Data Science or Machine Learning engineering experience, you should be good enough to dive in. I also assume you have basic knowledge of neural networks and linear algebra. For Python programmers familiar with Machine Learning and the basics of Deep Learning.

Название: Mathematical Aspects of Deep Learning
Автор: Philipp Grohs, Gitta Kutyniok
Издательство: Cambridge University Press
Год: 2023
Страниц: 492
Язык: английский
Формат: pdf
Размер: 22.3 MB

In recent years the development of new classification and regression algorithms based on Deep Learning (DL) has led to a revolution in the fields of Artificial Intelligence (AI), Machine Learning (ML), and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research.

Название: Ensemble Methods for Machine Learning (MEAP v8)
Автор: Gautam Kunapuli
Издательство: Manning Publications
Год: 2022
Страниц: 455
Язык: английский
Формат: pdf, epub
Размер: 25.5 MB

Many Machine Learning problems are too complex to be resolved by a single model or algorithm. Ensemble Machine Learning trains a group of diverse Machine Learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. Ensemble Machine Learning lets you make robust predictions without needing the huge datasets and processing power demanded by Deep Learning. It sets multiple models to work on solving a problem, combining their results for better performance than a single model working alone. This "wisdom of crowds" approach distils information from several models into a set of highly accurate results. For Python programmers with machine learning experience.

Название: Python How-To (MEAP v9)
Автор: Dr. Yong Cui
Издательство: Manning Publications
Год: 2022
Страниц: 606
Язык: английский
Формат: pdf, epub
Размер: 13.4 MB

Have you ever asked yourself, “How do I do that in Python?” If so, you’ll love this practical collection of the most important Python techniques. Python How-To walks you through the most important coding techniques in Python. Whether you’re doing data science, building web applications, or writing admin scripts, you’ll find answers to your “how-to” questions in this book. Author Yong Cui’s clear and practical writing is perfect for beginners and veterans alike, with insightful code snippets, interesting graphics, and challenging exercises. Along the way, you’ll learn how to take advantage of Python’s versatile tools and libraries. As one of the most popular languages, Python is the choice of language for many first-time coding learners. Its open-source, general-purpose, platform-independent nature has engendered probably the most active developer community, which has resulted in tens of thousands of freely available libraries for web development, Machine Learning (ML), Data Science, and many other specialties.

Название: Security as Code: DevSecOps Patterns with AWS (Final Release)
Автор: BK Sarthak Das, Virginia Chu
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 158
Язык: английский
Формат: epub (true), mobi
Размер: 10.1 MB

DevOps engineers, developers, and security engineers have ever-changing roles to play in today's cloud native world. In order to build secure and resilient applications, you have to be equipped with security knowledge. Enter security as code. In this book, authors BK Sarthak Das and Virginia Chu demonstrate how to use this methodology to secure any application and infrastructure you want to deploy. With Security as Code , you'll learn how to create a secure containerized application with Kubernetes using CI/CD tooling from AWS and open source providers. This practical book also provides common patterns and methods to securely develop infrastructure for resilient and highly available backups that you can restore with just minimal manual intervention.

Название: Concise Guide to Numerical Algorithmics: The Foundations and Spirit of Scientific Computing
Автор: John Lawrence Nazareth
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2023
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

Numerical Algorithmic Science and Engineering (NAS&E), or more compactly, Numerical Algorithmics, is the theoretical and empirical study and the practical implementation and application of algorithms for solving finite-dimensional problems of a numeric nature. The variables of such problems are either discrete-valued, or continuous over the reals, or, and as is often the case, a combination of the two, and they may or may not have an underlying network/graph structure. This re-emerging discipline of numerical algorithmics within computer science is the counterpart of the now well-established discipline of numerical analysis within mathematics, where the latter’s emphasis is on infinite-dimensional, continuous numerical problems and their finite-dimensional, continuous approximates.

Название: Computational Intelligence Applications for Software Engineering Problems
Автор: Parma Nand, Nitin Rakesh, Arun Prakash Agrawal
Издательство: CRC Press/Apple Academic Press
Год: 2023
Страниц: 325
Язык: английский
Формат: pdf (true)
Размер: 23.5 MB

This new volume explores the Computational Intelligence (CI) techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks can become costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering. Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using Machine Learning, Deep Learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.

Название: Physics with Excel and Python: Using the Same Data Structure Volume I: Basics, Exercises and Tasks
Автор: Dieter Mergel
Издательство: Springer
Год: 2022
Страниц: 493
Язык: английский
Формат: pdf (true)
Размер: 57.6 MB

This book is intended to serve as a basic introduction to scientific computing by treating problems from various areas of physics - mechanics, optics, acoustics, and statistical reasoning in the context of the evaluation of measurements. After working through these examples, students are able to independently work on physical problems that they encounter during their studies. For every exercise, the author introduces the physical problem together with a data structure that serves as an interface to programming in Excel and Python. When a solution is achieved in one application, it can easily be translated into the other one and presumably any other platform for scientific computing. This is possible because the basic techniques of vector and matrix calculation and array broadcasting are also achieved with spreadsheet techniques, and logical queries and for-loops operate on spreadsheets from simple Visual Basic macros. The key to all of the exercises is data structures, developed in introductory sections that explain the physical problems. They serve as an interface to both Excel and Python, and potentially also to other applications for scientific computation. To enable this approach, the Excel solutions in this edition use vectorized code and matrix formulas to mimic broadcasting, an essential Python technique for creating new arrays.

Название: Bio-Inspired Optimization in Fog and Edge Computing Environments: Principles, Algorithms, and Systems
Автор: Punit Gupta, Dinesh Kumar Saini, Pradeep Singh Rawat
Издательство: CRC Press
Год: 2023
Страниц: 269
Язык: английский
Формат: pdf (true)
Размер: 31.4 MB

Bio-Inspired Optimization in Fog and Edge Computing Environments covers novel and innovative solutions for Fog and Edge with Machine Learning (ML) and informatics-based technological solutions for various applications. Recently, nature- or bio-inspired techniques have emerged as a successful tool to understand and analyze collective behavior. Algorithms and mechanisms for the self- organization of complex natural systems have been used to solve optimization problems, particularly in complex systems that are adaptive, ever-evolving, and distributed in nature. What fits more perfectly into this scenario than the rapidly developing era of Fog and Edge computing? A new era of complexity science is emerging, in which nature- and bio-inspired principles are being applied to provide solutions. At the same time, the complexity of systems is increasing due to such models like the Internet of Things (IoT) and fog computing. Will complexity science, applying the principles of nature, be able to tackle the challenges posed by highly complex networked systems? Bio-Inspired Optimization in Fog and Edge Computing: Principles, Algorithms, and Systems is an attempt to answer this question.

Название: Acing the Certified Kubernetes Administrator Exam (MEAP V05)
Автор: Chad M. Crowell
Издательство: Manning Publications
Год: 2022
Страниц: 289
Язык: английский
Формат: pdf, epub
Размер: 24.4 MB

Becoming a Kubernetes administrator is a big accomplishment—and passing the Certified Kubernetes Administrator (CKA) exam can be a big boost to your career! Learn the hands-on skills you need to ace the exam with clear teaching and hands-on exercises that match the unique CKA test environment. Acing the Certified Kubernetes Administrator Exam is a fun, friendly guide to preparing for the CKA. If you’re familiar with Kubernetes, this book will ensure you’re ready to pass in just one month of study. If you’re brand new, this is the perfect primer to get started on your Kubernetes journey. The book pulls back the curtain on Kubernetes, explaining its complexities and relating its components to tech you probably already know. You’ll quickly get a Kubernetes cluster up and running, learn about common REST methods through the lens of Kubernetes, and master load balancing and networking—all vital skills to master for the CKA exam.