|
 |
|
 |
|
|
 |
|  |
|
 Название: Advanced Mathematical Applications in Data Science
Автор: Biswadip Basu Mallik, Kirti Verma, Rahul Kar, Ashok Kumar Shaw
Издательство: Bentham Books
Год: 2023
Страниц: 223
Язык: английский
Формат: pdf (true), epub
Размер: 27.1 MB
Advanced Mathematical Applications in Data Science comprehensively explores the crucial role mathematics plays in the field of Data Science. Each chapter is contributed by scientists, researchers, and academicians. The 13 chapters cover a range of mathematical concepts utilized in Data Science, enabling readers to understand the intricate connection between mathematics and data analysis. The book covers diverse topics, including, Machine Learning models, the Kalman filter, data modeling, artificial neural networks, clustering techniques, and more, showcasing the application of advanced mathematical tools for effective data processing and analysis. With a strong emphasis on real-world applications, the book offers a deeper understanding of the foundational principles behind data analysis and its numerous interdisciplinary applications. This reference is an invaluable resource for graduate students, researchers, academicians, and learners pursuing a research career in mathematical computing or completing advanced data science courses. An Artificial Neural Network (ANN) is a data processing paradigm inspired by the way organic nervous systems, such as the brain, process data. | |
Разместил: Ingvar16 1-10-2023, 16:49 | Комментарии: 0 | Подробнее
| | | |
 |
|  |
|
|
|
|
|
|
| |
|
 Название: Numerical Machine Learning
Автор: Zhiyuan Wang, Sayed Ameenuddin Irfan, Christopher Teoh
Издательство: Bentham Books
Год: 2023
Страниц: 225
Язык: английский
Формат: pdf (true), epub
Размер: 32.3 MB
Numerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used machine learning algorithms and techniques, including linear regression, regularization, logistic regression, decision trees, gradient boosting, Support Vector Machine, and K-means Clustering. Through a step-by-step exploration of concrete numerical examples, the students (primarily undergraduate and graduate students studying machine learning) can develop a well-rounded understanding of these algorithms, gain an in-depth knowledge of how the mathematics relates to the implementation and performance of the algorithms, and be better equipped to apply them to practical problems. From our experiences of teaching Machine Learning using various textbooks, we have noticed that there tends to be a strong emphasis on abstract mathematics when discussing the theories of Machine Learning algorithms. On the other hand, in the application of Machine Learning, it usually straightaway goes to import offthe- shelf libraries such as scikit-learn, TensorFlow, Keras, and PyTorch. | |
Разместил: Ingvar16 1-10-2023, 16:18 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Processing for Android: Create Mobile, Sensor-aware, and XR Applications Using Processing, 2nd Edition
Автор: Andres Colubri
Издательство: Apress
Год: 2023
Страниц: 401
Язык: английский
Формат: pdf, epub
Размер: 42.0 MB
Learn how to use the Processing programming language and environment to create Android applications with ease. This book covers the basics of the Processing language, allowing users to effectively program interactive graphics in 2D, 3D, and Extended Reality (XR). It also details the application of these techniques to different types of Android devices (smartphones, tablets, wearables, and smartwatches). This updated edition walks you through the entire process of creating an app, from the initial idea to release of the final app via the Google Play App Store. Over the course of the book, you’ll learn to write engaging apps driven by user interaction and sensor data. A comprehensive series of hands-on projects, ranging from simple sketches to more complex projects involving shaders, VR, and AR will give you the firsthand experience you need to begin developing your own projects. And once you have your Processing projects completed, you’ll be able to upload them to the Google Play store to be shared with the world! | |
Разместил: Ingvar16 30-09-2023, 19:57 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: The DevSecOps Playbook: Deliver Continuous Security at Speed
Автор: Sean D. Mack
Издательство: Wiley
Год: 2024
Страниц: 241
Язык: английский
Формат: pdf (true), djvu
Размер: 10.2 MB
An essential and up-to-date guide to DevSecOps. In The DevSecOps Playbook: Deliver Continuous Security at Speed, the Chief Information and Information Security Officer at Wiley, Sean D. Mack, delivers an insightful and practical discussion of how to keep your business secure. You'll learn how to leverage the classic triad of people, process, and technology to build strong cybersecurity infrastructure and practices. You'll also discover the shared responsibility model at the core of DevSecOps as you explore the principles and best practices that make up contemporary frameworks. The book explains why it's important to shift security considerations to the front-end of the development cycle and how to do that, as well as describing the evolution of the standard security model over the last few years and how that has impacted modern cybersecurity. | |
Разместил: Ingvar16 30-09-2023, 16:40 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Applications of Optimization and Machine Learning in Image Processing and IoT
Автор: Nidhi Gupta
Издательство: CRC Press
Год: 2024
Страниц: 236
Язык: английский
Формат: pdf (true)
Размер: 10.8 MB
This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and Machine Learning in image processing and IoT. Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of Machine Learning, IoT and image processing. The field of Computer Science with the fastest growth right now is Machine Learning, which has applications in fields as varied as marketing, health-care, production, cybersecurity and mobility. Three elements are readily available and combined: (1) faster and more potent part of a computer, like multiple cores and broad sense GPU; (2) a computer program that utilizes these computational structures; and (3) essentially unlimited training data sets for a certain issue, like digital photos, digitalized files. The two stages of a computer-vision-based Machine Learning process are feature extraction and classification. Additional Machine Learning models, including ANN, CNN, RNN and others, can be applied for system training and optimization. | |
Разместил: Ingvar16 30-09-2023, 15:37 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Visual Object Tracking using Deep Learning
Автор: Ashish Kumar
Издательство: CRC Press
Год: 2024
Страниц: 216
Язык: английский
Формат: pdf (true)
Размер: 20.3 MB
This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. Over the past few years, visual tracking algorithms are evolved from conventional frameworks to deep learning-based frameworks. Conventional trackers are fast in processing but are not effective for tedious environmental variations. Conventional trackers are explored as probabilistic, generative, discriminative, and deterministic frameworks. In a direction to improve tracking accuracy, the collaborative and multi-stage tracking frameworks are analyzed for real-time outcomes for tedious tracking problems. Deep Learning trackers provide discriminative features with efficient performance in complex tracking variations. It became necessary to extract the salient features in target appearance models using various deep neural networks. | |
Разместил: Ingvar16 30-09-2023, 15:10 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Microservices with Spring Boot and Spring Cloud: Develop modern, resilient, scalable and highly available apps using microservices with Java, Spring Boot 3.0 and Spring Cloud
Автор: Tejaswini Jog, Mandar Jog
Издательство: Orange Education Pvt Ltd, AVA
Год: September 2023
Страниц: 357
Язык: английский
Формат: epub (true)
Размер: 11.7 MB
Microservices has emerged as a powerful solution to build flexible, scalable, and resilient applications. This Book is the go-to-guide to understanding, designing, and implementing microservice architectures using Spring Boot. It takes you on a journey through the intricacies of microservices to create robust and efficient microservice-based applications. This book helps you to understand the motivations and the entire process behind migrating from monolithic to microservice architectures. It covers essentials like REST basics, advanced topics such as centralized configuration, inter-service communication, Eureka Server, resilience mechanisms, security, and Docker deployment. Readers will be equipped to effortlessly find and access instances within a microservice architecture without disrupting clients. You will delve into distributed tracing and its importance in monitoring the interactions among microservices. Finally, we will discuss strategies for ensuring the reliability of your microservices architecture. | |
Разместил: Ingvar16 30-09-2023, 14:44 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Building Knowledge Graphs: A Practitioner's Guide (Final)
Автор: Jesus Barrasa, Maya Natarajan, Jim Webber
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 291
Язык: английский
Формат: True PDF, True EPUB (Retail Copy)
Размер: 28.5 MB
Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by storing interlinked descriptions of entities—objects, events, situations, or abstract concepts—and encoding the underlying information. How do you create a knowledge graph? And how do you move it from theory into production? Graph data has become ubiquitous in the last decade. Graphs underpin everything from consumer-facing systems like navigation and social networks to critical infrastructure like supply chains and policing. A consistent theme has emerged: applying knowledge in context is the single most powerful tool that most businesses have. Through research and experience, a set of patterns and practices called knowledge graphs has been developed to support extracting knowledge from data of all types and in all sources, from systems of record to frozen data lakes to application logs. | |
Разместил: Ingvar16 30-09-2023, 05:07 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
Название: Математика в машинном обучении
Автор: Марк Питер Дайзенрот, А. Альдо Фейзал, Чен Сунь Он
Издательство: Питер
Год: 2024
Формат: pdf
Страниц: 512
Для сайта: Mirknig.su
Размер: 17,2 Мб
Язык: русский
Фундаментальные математические дисциплины, необходимые для понимания машинного обучения, — это линейная алгебра, аналитическая геометрия, векторный анализ, оптимизация, теория вероятностей и статистика. Традиционно все эти темы размазаны по различным курсам, поэтому студентам, изучающим data science или computer science, а также профессионалам в МО, сложно выстроить знания в единую концепцию. Эта книга самодостаточна: читатель знакомится с базовыми математическими концепциями, а затем переходит к четырем основным методам МО: линейной регрессии, методу главных компонент, гауссову моделированию и методу опорных векторов. Тем, кто только начинает изучать математику, такой подход поможет развить интуицию и получить практический опыт в применении математических знаний, а для читателей с базовым математическим образованием книга послужит отправной точкой для более продвинутого знакомства с машинным обучением. | |
Разместил: relizer 29-09-2023, 20:09 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Learning Git: A Hands-On and Visual Guide to the Basics of Git (Final)
Автор: Anna Skoulikari
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 321
Язык: английский
Формат: True PDF, True EPUB (Retail Copy)
Размер: 19.6 MB
This book teaches Git in a simple, visual, and tangible manner so that you can build a solid mental model of how Git version control works. Through the use of color, storytelling, and hands-on exercises, you will learn to use this tool with confidence. The information is introduced incrementally so that you don't get bogged down with unknown terms or concepts. Learning Git is ideal for anyone who needs to use Git for personal or professional projects: coding bootcamp students, junior developers, data professionals, and technical writers, to name just a few! This book is for anyone who wants to learn the basics of how Git works. It is especially designed for individuals that are just getting started learning technical skills, or that work in nontechnical roles but need to use Git to collaborate with their technical counterparts. Some examples of individuals that may benefit from this book include (but are not limited to) coding bootcamp students, computer science students, technical writers, product managers, designers, junior developers, data scientists, and self-taught programmers. | |
Разместил: Ingvar16 29-09-2023, 18:13 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
Навигация
Вход на сайт
Реклама
