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Математика для Data Science

Автор: hottei83 от 2022-03-15, 16:12:19
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Математика для Data Science Название: Математика для Data Science
Автор: Михаил Миронов, Екатерина Минеева
Язык: Русский
Издательство: Издательские решения
Жанр: программирование, разработка, компьютерная литература
Год: 2021
Страниц: 122
Формат: PDF + PNG
Размер: 50.07 Mb

Описание:
Разберитесь, как работают технологии машинного обучения, и научитесь пользоваться ими осознанно.

Q# Pocket Guide: Instant Help for Q# Developers (Fifth Early Release)

Автор: Limpopo5 от 2022-02-10, 06:41:07
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Q# Pocket Guide: Instant Help for Q# Developers (Fifth Early Release)Название: Q# Pocket Guide: Instant Help for Q# Developers (Fifth Early Release)
Автор: Mariia Mykhailova
Издательство: O’Reilly Media, Inc.
Год: 2022-02-08
Страниц: 151
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

Q# is a domain-specific language for quantum programming that combines familiar "classical" language constructs with quantum-specific ones. Ideal for any developer familiar with, or willing to learn, the basics of quantum computing, this pocket guide quickly helps you find syntax and usage information for unfamiliar aspects of Q#. You'll explore the quantum software development lifecycle, from implementing the program to testing and debugging it to running it on quantum hardware, and you'll learn to use the tools provided by Microsoft's Quantum Development Kit for each step of the process.

DevOps Tools for Java Developers: Best Practices from Source Code to Production Containers (Fifth Early Release)

Автор: Limpopo5 от 2022-02-04, 07:07:27
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DevOps Tools for Java Developers: Best Practices from Source Code to Production Containers (Fifth Early Release)Название: DevOps Tools for Java Developers: Best Practices from Source Code to Production Containers (Fifth Early Release)
Автор: Stephen Chin, Melissa McKay, Ixchel Ruiz
Издательство: O’Reilly Media, Inc.
Год: 2022-02-03
Страниц: 348
Язык: английский
Формат: epub
Размер: 25.8 MB

With the rise of DevOps, low-cost cloud computing, and container technologies, the way Java developers approach development today has changed dramatically. This practical guide helps you take advantage of microservices, serverless, and cloud native technologies using the latest DevOps techniques to simplify your build process and create hyperproductive teams. Stephen Chin, Melissa McKay, Ixchel Ruiz, and Baruch Sadogursky help you evaluate an array of options. The list includes source control with Git, build declaration with Maven and Gradle, CI/CD with CircleCI, package management with Artifactory, containerization with Docker and Kubernetes, and much more. Whether you're building applications with Jakarta EE, Spring Boot, Dropwizard, MicroProfile, Micronaut, or Quarkus, this comprehensive guide has you covered.

Beginning Deep Learning with TensorFlow: Work with Keras, MNIST Data Sets, and Advanced Neural Networks

Автор: Limpopo5 от 2022-01-28, 22:00:15
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Beginning Deep Learning with TensorFlow: Work with Keras, MNIST Data Sets, and Advanced Neural NetworksНазвание: Beginning Deep Learning with TensorFlow: Work with Keras, MNIST Data Sets, and Advanced Neural Networks
Автор: Liangqu Long, Xiangming Zeng
Издательство: Apress
Год: 2022
Страниц: 727
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB

Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners. You’ll start with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically.

Machine Learning and Optimization Models for Optimization in Cloud

Автор: Limpopo5 от 2022-01-28, 21:03:07
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Machine Learning and Optimization Models for Optimization in CloudНазвание: Machine Learning and Optimization Models for Optimization in Cloud
Автор: Punit Gupta, Mayank K. Goyal
Издательство: CRC Press
Год: 2022
Страниц: 219
Язык: английский
Формат: pdf (true)
Размер: 15.1 MB

Machine Learning and Models for Optimization in Cloud’s main aim is to meet the user requirement with high quality of service, least time for computation and high reliability. With increase in services migrating over cloud providers, the load over the cloud increases resulting in fault and various security failure in the system results in decreasing reliability. To fulfill this requirement cloud system uses intelligent metaheuristic and prediction algorithm to provide resources to the user in an efficient manner to manage the performance of the system and plan for upcoming requests. Intelligent algorithm helps the system to predict and find a suitable resource for a cloud environment in real time with least computational complexity taking into mind the system performance in under loaded and over loaded condition.

Programming ML.NET

Автор: Limpopo5 от 2022-01-24, 04:02:46
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Programming ML.NETНазвание: Programming ML.NET
Автор: Dіnо Еsроsіtо, Frаnсеsсо Еsроsіtо
Издательство: Microsoft Press/Pearson Education
Год: 2022
Страниц: 256
Язык: английский
Формат: pdf, epub
Размер: 16.4 MB

With .NET 5’s ML.NET and Programming ML.NET, any Microsoft .NET developer can solve serious machine learning problems, increasing their value and competitiveness in some of today’s fastest-growing areas of software development. World-renowned Microsoft development expert Dino Esposito covers everything you need to know about ML.NET, the machine learning pipeline, and real-world machine learning solutions development. Modeled on his popular Programming ASP.NET books, this guide takes the same scenario-based approach Microsoft’s team used to build the ML.NET framework itself. Esposito presents and illuminates ML.NET’s dedicated mini-frameworks (“ML Tasks”) for specific classes of problems, and draws on personal experience to help developers apply these in the real world, where a problem’s complexity can vary widely based on data availability or the specific results you need. In a full section on ML.NET neural networks, Esposito introduces key concepts and presents realistic examples you can reuse in your own applications. Along the way, Esposito also shows how to leverage powerful Python-based machine learning tools in the .NET environment.

Learn to Code with Scratch: Let Your Kids' Creative Ideas Come to Life by Coding Them into Programs

Автор: Limpopo5 от 2022-01-23, 01:03:36
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Learn to Code with Scratch: Let Your Kids' Creative Ideas Come to Life by Coding Them into ProgramsНазвание: Learn to Code with Scratch: Let Your Kids' Creative Ideas Come to Life by Coding Them into Programs
Автор: Muskan Arora
Издательство: BPB Publications
Год: 2022
Страниц: 207
Язык: английский
Формат: pdf, epub
Размер: 16.3 MB

Enjoy making games and apps through coding and boost your computational thinking. 'Learn to Code with Scratch' prepares your child to begin building cool apps, games, animated stories, quizzes, and a variety of other enjoyable applications. This book teaches your child what a programme is and how it works using Scratch, a comprehensive visual programming language. This book teaches your child how to connect various code blocks and establish the program's logic by using seven distinct games and applications, including a haunted party, a talking robot, a mystical story, and a humorous quiz game. You will learn how to write and create a programme in Scratch and how to run your programme and save and share it with your loved ones.

Issues With Facial Recognition Technology

Автор: Limpopo5 от 2022-01-22, 19:50:08
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Issues With Facial Recognition TechnologyНазвание: Issues With Facial Recognition Technology
Автор: Warren Lambert
Издательство: Nova Science Publishers
Год: 2021
Страниц: 232
Язык: английский
Формат: pdf (true)
Размер: 11.7 MB

Automated facial recognition systems compare two or more images of faces to determine whether they represent the same individual. Facial recognition technology (FRT) falls within the larger categories of biometric technology used to varying degrees by the government and private entities to identify persons. This book deals with some of the issues concerning facial recognition technology. Biometric technology uses automated processes to identify an individual through unique physical characteristics, such a fingerprints, speech patterns, or facial features. FRT can perform several functions, with the most common being face identification - the comparison of an unknown person’s face against a gallery of known persons - and face verification—confirmation of someone’s claimed identity. When an image of an unknown person is compared to a database, the technology may determine that an image in the database is sufficiently similar to register as a likely match. One or more likely matches may be identified. If no images are found to be sufficiently similar, the system will return no matches. Face identification can be used for surveillance, to find a person of interest, or for the identification of subjects who are either unable or unwilling to respond.

Personalized Machine Learning

Автор: Limpopo5 от 2022-01-22, 19:44:13
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Personalized Machine LearningНазвание: Personalized Machine Learning
Автор: Julian McAuley
Издательство: Cambridge University Press
Год: 2022
Страниц: 337
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Every day we interact with Machine Learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' Machine Learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.

Principles of Incident Response and Disaster Recovery, 3rd Edition

Автор: Limpopo5 от 2022-01-22, 19:38:12
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Principles of Incident Response and Disaster Recovery, 3rd EditionНазвание: Principles of Incident Response and Disaster Recovery, 3rd Edition
Автор: М.Е. Whіtmаn,
Издательство: Cengage Learning
Год: 2021
Страниц: 418
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Learn how to identify vulnerabilities within computer networks and implement countermeasures that mitigate risks and damage with Whitman/Mattord's PRINCIPLES OF INCIDENT RESPONSE & DISASTER RECOVERY, 3rd Edition. This edition offers the knowledge you need to help organizations prepare for and avert system interruptions and natural disasters. Comprehensive coverage addresses information security and IT in contingency planning today. Updated content focuses on incident response and disaster recovery. You examine the complexities of organizational readiness from an IT and business perspective with emphasis on management practices and policy requirements. You review industry's best practices for minimizing downtime in emergencies and curbing losses during and after system service interruptions. This edition includes the latest NIST knowledge, expanded coverage of security information and event management (SIEM) and unified threat management, and more explanation of cloud-based systems and Web-accessible tools to prepare you for success.

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