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 Название: MATLAB Deep Learning Toolbox User’s Guide (R2022b)
Автор: Beale M.H., Hagan M.T., Demuth H.B.
Издательство: The MathWorks, Inc.
Год: 2022
Формат: PDF
Страниц: 4452
Размер: 94,7 Mb
Язык: English
Deep Learning (DL) is a branch of Machine Learning (ML) that teaches computers to do what comes naturally to humans: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. Deep Learning is especially suited for image recognition, which is important for solving problems such as facial recognition, motion detection, and many advanced driver assistance technologies such as autonomous driving, lane detection, pedestrian detection, and autonomous parking.
Deep Learning Toolbox provides simple MATLAB commands for creating and interconnecting the layers of a deep neural network. Examples and pretrained networks make it easy to use MATLAB for deep learning, even without knowledge of advanced computer vision algorithms or neural networks. | |
Разместил: vitvikvas 21-09-2022, 16:16 | Комментарии: 0 | Подробнее
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 Название: A Guide to MATLAB for ME 160
Автор: Austin Bray and Reza Montazami
Издательство: Iowa State University Digital Press
Год: 2022
Формат: True PDF
Страниц: 81
Размер: 10 Mb
Язык: English
This textbook provides an introduction to the MATLAB programming language for first-year mechanical engineering students enrolled in ME 160, Mechanical Engineering Problem Solving with Computer Applications. Designed to follow the content taught in class, this book provides a supplement to in-class learning that is presented at a level that is understandable to a student with no experience coding before coming to Iowa State University. | |
Разместил: vitvikvas 21-09-2022, 15:11 | Комментарии: 0 | Подробнее
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 Название: Handbook of Research on Artificial Intelligence in Human Resource Management
Автор: Stefan Strohmeier
Издательство: Edward Elgar Publishing Limited
Год: 2022
Формат: True PDF
Страниц: 417
Размер: 10 Mb
Язык: English
This cutting-edge Handbook offers a comprehensive introduction to the emerging research field of artificial intelligence (AI) in human resource management (HRM). Broadly mapping AI fields relevant for HR, it not only considers the more well-known areas of machine learning and natural language processing, but also lesser-known fields such as affective computing and robotic process automation.
Expert contributors analyze the applications of machine learning in human resources, including machine learning on text data, audio and video data, social media data, and in recruiting and staffing. They also explore a range of innovative topics such as knowledge representation and reasoning, and evolutionary computing. Discussing the explainability, fairness, accountability, and legitimacy of AI in HR, chapters bring normative issues to the fore. Approaches to researching AI in HR and to employing AI in HR research are also tackled. Offering an insight into existing research on artificial intelligence in human resources, the Handbook introduces core issues and considers implications for future research. | |
Разместил: vitvikvas 21-09-2022, 10:57 | Комментарии: 0 | Подробнее
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 Название: Operating OpenShift (Early Release)
Автор: Rick Rackow and Manuel Dewald
Издательство: O’Reilly Media
Год: 2022-09-20: Third Release
Формат: ePUB
Размер: 10 Mb
Язык: English
Kubernetes has gained significant popularity over the past few years, with OpenShift as one of its most mature and prominent distributions. But while OpenShift provides several layers of abstraction over vanilla Kubernetes, this software can quickly become overwhelming because of its rich feature set and functionality. This practical book helps you understand and manage OpenShift clusters from minimal deployment to large multicluster installations.
Principal site reliability engineers Rick Rackow and Manuel Dewald, who worked together on Red Hat's managed OpenShift offering for years, provide valuable advice to help your teams operate OpenShift clusters efficiently. Designed for SREs, system administrators, DevOps engineers, and cloud architects, Operating OpenShift encourages consistent and easy container orchestration and helps reduce the effort of deploying a Kubernetes platform. You'll learn why OpenShift has become highly attractive to enterprises large and small. | |
Разместил: vitvikvas 21-09-2022, 07:18 | Комментарии: 0 | Подробнее
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 Название: Terraform: Up & Running: Writing Infrastructure as Code, 3rd Edition (Final)
Автор: Yevgeniy Brikman
Издательство: O’Reilly Media, Inc.
Год: 2022
Страниц: 585
Язык: английский
Формат: pdf (true), epub
Размер: 17.0 MB
Terraform has become a key player in the DevOps world for defining, launching, and managing infrastructure as code (IaC) across a variety of cloud and virtualization platforms, including AWS, Google Cloud, Azure, and more. This hands-on third edition, expanded and thoroughly updated for version 1.0 and beyond, shows you the fastest way to get up and running with Terraform. Gruntwork cofounder Yevgeniy (Jim) Brikman takes you through code examples that demonstrate Terraform's simple, declarative programming language for deploying and managing infrastructure with a few commands. Veteran sysadmins, DevOps engineers, and novice developers will quickly go from Terraform basics to running a full stack that can support a massive amount of traffic and a large team of developers. | |
Разместил: Ingvar16 20-09-2022, 15:04 | Комментарии: 0 | Подробнее
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 Название: Advanced Metaheuristic Algorithms and Their Applications in Structural Optimization
Автор: Ali Kaveh, Kiarash Biabani Hamedani
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2022
Страниц: 369
Язык: английский
Формат: pdf (true)
Размер: 17.1 MB
The main purpose of the present book is to develop a general framework for population-based metaheuristics based on some basic concepts of set theory. The idea of the framework is to divide the population of individuals into subpopulations of identical sizes. Therefore, in each iteration of the search process, different subpopulations explore the search space independently but simultaneously. The framework aims to provide a suitable balance between exploration and exploitation during the search process. A few chapters containing algorithm-specific modifications of some state-of-the-art metaheuristics are also included to further enrich the book. | |
Разместил: Ingvar16 20-09-2022, 13:43 | Комментарии: 0 | Подробнее
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 Название: Programming with Python
Автор: T.R. Padmanabhan
Издательство: Springer
Год: 2016
Страниц: 349
Язык: английский
Формат: pdf (true), epub
Размер: 18.2 MB
Based on the latest version of the language, this book offers a self-contained, concise and coherent introduction to programming with Python. The book’s primary focus is on realistic case study applications of Python. Each practical example is accompanied by a brief explanation of the problem-terminology and concepts, followed by necessary program development in Python using its constructs, and simulated testing. Given the open and participatory nature of development, Python has a variety of incorporated data structures, which has made it difficult to present it in a coherent manner. Further, some advanced concepts (super, yield, generator, decorator, etc.) are not easy to explain. The book specially addresses these challenges; starting with a minimal subset of the core, it offers users a step-by-step guide to achieving proficiency. So embrace Python—the language by the people, of the people, for the people. | |
Разместил: Ingvar16 20-09-2022, 11:51 | Комментарии: 0 | Подробнее
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 Название: Reliable Machine Learning
Автор: Cathy Chen, Niall Richard Murphy, Kranti Parisa, D. Sculley and Todd Underwood
Издательство: O’Reilly Media
Год: 2022
Формат: ePUB
Размер: 10 Mb
Язык: English
Whether you're part of a small startup or a planet-spanning megacorp, this practical book shows data scientists, SREs, and business owners how to run ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization. | |
Разместил: vitvikvas 20-09-2022, 10:29 | Комментарии: 0 | Подробнее
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 Название: Deep Learning for Social Media Data Analytics
Автор: Tzung-Pei Hong, Leticia Serrano-Estrada, Akrati Saxena, Anupam Biswas
Издательство: Springer
Год: 2022
Формат: True PDF
Страниц: 297
Размер: 10 Mb
Язык: English
This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics. | |
Разместил: vitvikvas 20-09-2022, 09:22 | Комментарии: 0 | Подробнее
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 Название: Security as Code: DevSecOps Patterns with AWS (Second Early Release)
Автор: BK Sarthak Das, Virginia Chu
Издательство: O’Reilly Media, Inc.
Год: 2022-09-20
Язык: английский
Формат: epub (true), mobi
Размер: 10.2 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. | |
Разместил: Ingvar16 20-09-2022, 02:08 | Комментарии: 0 | Подробнее
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