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Название: Graph-Powered Analytics and Machine Learning with TigerGraph
Автор: Victor Lee, Phuc Kien Nguyen and Xinyu Chang
Издательство: O’Reilly Media
Год: 2022-10-06: Seventh Release
Формат: ePUB
Размер: 15,1 Mb
Язык: English

With the rapid rise of graph databases, organizations are now implementing advanced analytics and machine learning solutions to help drive business outcomes. This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database models available.
You'll explore a three-stage approach to deriving value from connected dаta: connect, analyze, and learn. Victor Lee, Xinyu Chan, and Gaurav Deshpande from TigerGraph present real use cases covering several contemporary business needs. By diving into hands-on exercises using TigerGraph Cloud, you'll quickly become proficient at designing and managing advanced analytics and machine learning solutions for your organization.
Use graph thinking to connect, analyze, and learn from data for advanced analytics and machine learning
Learn how graph analytics and machine learning can deliver key business insights and outcomes
Use five core categories of graph algorithms to drive advanced analytics and machine learning
Deliver a real-time 360-degree view of core business entities, including customer, product, service, supplier, and citizen
Разместил: vitvikvas 30-09-2022, 18:55 | Комментарии: 0 | Подробнее
Название: Functional and Concurrent Programming: Core Concepts and Features
Автор: Charpntier
Издательство: Pearson
Год: 2022
Формат: True ePUB, MOBI
Страниц: 258
Размер: 10 Mb
Язык: English

The functional and concurrent programming language features supported by modern languages can be challenging, even for experienced developers. These features may appear intimidating to OOP programmers because of a misunderstanding of how they work. Programmers first need to become familiar with the abstract concepts that underlie these powerful features.
In Functional and Concurrent Programming, Michel Charpentier introduces a core set of programming language constructs that will help you be productive in a variety of programming languagesnow and in the future. Charpentier illustrates key concepts with numerous small, focused code examples, written in Scala, and with case studies that provide a thorough grounding in functional and concurrent programming skills. These skills will carry from language to languageincluding the most recent incarnations of Java. Using these features will enable developers and programmers to write high-quality code that is easier to understand, debug, optimize, and evolve.
Разместил: vitvikvas 30-09-2022, 18:37 | Комментарии: 0 | Подробнее
Object Oriented Modeling and Design Using UML, 2nd EditionНазвание: Object Oriented Modeling and Design Using UML, 2nd Edition
Автор: Ajit Singh, Anamika
Издательство: Independently published
Год: 2022
Страниц: 220
Язык: английский
Формат: epub
Размер: 10.2 MB

This book starts with requirements gathering & ends with implementation. In the process, you'll learn how to analyze and design classes, their relationships to each other in order to build a model of the problem domain. You'll also use common UML diagrams throughout this process, such as use-case, class, activity & other diagrams. This book is also suitable for use in postgraduate and graduate courses as well as in professional seminars and individual study. Because it deals primarily with a method of software development, it is most appropriate for courses in software engineering and as a supplement to courses involving specific object-oriented programming languages. The Unified Modeling Language™ (UML) is inherently object-oriented modeling language and was designed for use in object-oriented software applications. The applications could be based on the object-oriented technologies recommended by the Object Management Group (OMG), which owns the UML.
Разместил: Ingvar16 30-09-2022, 18:37 | Комментарии: 0 | Подробнее
Federated Learning Over Wireless Edge NetworksНазвание: Federated Learning Over Wireless Edge Networks
Автор: Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong
Издательство: Springer
Год: 2022
Страниц: 175
Язык: английский
Формат: pdf
Размер: 10.1 MB

This book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks. This provides readers with a concise introduction to the challenges and state-of-the-art approaches towards implementing FL over the wireless edge network. Then, in consideration of resource heterogeneity at the network edge, the authors provide multifaceted solutions at the intersection of network economics, game theory, and Machine Learning towards improving the efficiency of resource allocation for FL over the wireless edge networks. The confluence of edge computing and Artificial Intelligence (AI) has driven the rise of edge intelligence, which leverages the storage, communication, and computation capabilities of end devices and edge servers to empower AI implementation at scale closer to where data is generated. An enabling technology of edge intelligence is the privacy-preserving Machine Learning (ML) paradigm known as Federated Learning (FL).
Разместил: Ingvar16 30-09-2022, 14:54 | Комментарии: 0 | Подробнее
Improving Classifier Generalization: Real-Time Machine Learning based ApplicationsНазвание: Improving Classifier Generalization: Real-Time Machine Learning based Applications
Автор: Rahul Kumar Sevakula, Nishchal K. Verma
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 181
Язык: английский
Формат: pdf
Размер: 10.1 MB

This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies. The book specifically provides a detailed tutorial on how to approach time-series classification problems and discusses two real time case studies on condition monitoring. In addition to describing the various aspects a data scientist must consider before finalizing their approach to a classification problem and reviewing the state of the art for improving classification generalization performance, it also discusses in detail the authors own contributions to the field, including MVPC - a classifier with very low VC dimension, a graphical indices based framework for reliable predictive maintenance and a novel general-purpose membership functions for Fuzzy Support Vector Machine which provides state of the art performance with noisy datasets, and a novel scheme to introduce Deep Learning (DL) in Fuzzy Rule based classifiers (FRCs). This monograph begins with the fundamentals of classifiers, bias-variance tradeoff, statistical learning theory (SLT), probably approximate correct (PAC) framework, maximum margin classifiers, and popular methods which improve generalization like regularization, boosting, transfer learning, dropout in Deep Learning, etc. Furthermore, the monograph solves four independent problems that have great relevance for certain real-time applications.
Разместил: Ingvar16 30-09-2022, 14:38 | Комментарии: 0 | Подробнее
AI powered Search (MEAP V13)Название: AI powered Search (MEAP V13)
Автор: Trey Grainger, Doug Turnbull, Max Irwin
Издательство: Manning Publications
Год: 2022
Страниц: 355
Язык: английский
Формат: pdf (true)
Размер: 33.2 MB

AI-Powered Search teaches you the latest machine learning techniques to create search engines that continuously learn from your users and your content, to drive more domain-aware and intelligent search. Today’s search engines are expected to be smart, understanding the nuances of natural language queries, as well as each user’s preferences and context. AI-Powered Search is an authoritative guide to applying leading-edge data science techniques to search.
Разместил: Ingvar16 30-09-2022, 12:13 | Комментарии: 0 | Подробнее
Название: Robotics for Programmers (MEAP)
Автор: Andreas Bihlmaier
Издательство: Manning Publications
Год: 2022 V04
Формат: True PDF
Страниц: 252
Размер: 13,1 Mb
Язык: English

Master the skills you need to program robots and other mechanical systems. Interesting examples and clear explanations guide you through programming robot arms, robots that drive and fly, and mobile manipulators.
Разместил: vitvikvas 30-09-2022, 12:04 | Комментарии: 0 | Подробнее
Ensemble Methods for Machine Learning (MEAP 6)Название: Ensemble Methods for Machine Learning (MEAP 6)
Автор: Gautam Kunapuli
Издательство: Manning Publications
Год: 2022
Страниц: 320
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB

In Ensemble Methods for Machine Learning you'll learn to implement the most important ensemble machine learning methods from scratch. 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.
Разместил: Ingvar16 30-09-2022, 12:01 | Комментарии: 0 | Подробнее
Kubernetes for Developers (MEAP v11)Название: Kubernetes for Developers (MEAP v11)
Автор: William Denniss
Издательство: Manning Publications
Год: 2022
Страниц: 291
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Kubernetes for Developers is a hands-on guide to taking your first steps into Kubernetes using the powerful Google Kubernetes Engine service. Kubernetes for Developers is a clear and practical beginner’s guide that shows you just how easy, flexible, and cost-effective it can be to make the switch to Kubernetes deployment even for small to medium-sized applications.
Разместил: Ingvar16 30-09-2022, 11:52 | Комментарии: 0 | Подробнее
Название: Evolutionary Deep Learning: Genetic algorithms and neural networks (MEAP)
Автор: Micheal Lanham
Издательство: Manning Publications
Год: 2022 V10
Формат: True PDF
Страниц: 309
Размер: 13,1 Mb
Язык: English

Discover one-of-a-kind AI strategies never before seen outside of academic papers! Learn how the principles of evolutionary computation overcome deep learning’s common pitfalls and deliver adaptable model upgrades without constant manual adjustment. Evolutionary Deep Learning is a guide to improving your deep learning models with AutoML enhancements based on the principles of biological evolution. This exciting new approach utilizes lesser- known AI approaches to boost performance without hours of data annotation or model hyperparameter tuning.
Google Colab notebooks make it easy to experiment and play around with each exciting example. By the time you’ve finished reading Evolutionary Deep Learning, you’ll be ready to build deep learning models as self-sufficient systems you can efficiently adapt to changing requirements.
Разместил: vitvikvas 30-09-2022, 11:50 | Комментарии: 0 | Подробнее



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