Author: Jarred Capellman
Publisher: Packt Publishing Ltd
ISBN: 1789804299
Category : Computers
Languages : en
Pages : 287

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Book Description
Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET Core Key FeaturesGet well-versed with the ML.NET framework and its components and APIs using practical examplesLearn how to build, train, and evaluate popular machine learning algorithms with ML.NET offeringsExtend your existing machine learning models by integrating with TensorFlow and other librariesBook Description Machine learning (ML) is widely used in many industries such as science, healthcare, and research and its popularity is only growing. In March 2018, Microsoft introduced ML.NET to help .NET enthusiasts in working with ML. With this book, you’ll explore how to build ML.NET applications with the various ML models available using C# code. The book starts by giving you an overview of ML and the types of ML algorithms used, along with covering what ML.NET is and why you need it to build ML apps. You’ll then explore the ML.NET framework, its components, and APIs. The book will serve as a practical guide to helping you build smart apps using the ML.NET library. You’ll gradually become well versed in how to implement ML algorithms such as regression, classification, and clustering with real-world examples and datasets. Each chapter will cover the practical implementation, showing you how to implement ML within .NET applications. You’ll also learn to integrate TensorFlow in ML.NET applications. Later you’ll discover how to store the regression model housing price prediction result to the database and display the real-time predicted results from the database on your web application using ASP.NET Core Blazor and SignalR. By the end of this book, you’ll have learned how to confidently perform basic to advanced-level machine learning tasks in ML.NET. What you will learnUnderstand the framework, components, and APIs of ML.NET using C#Develop regression models using ML.NET for employee attrition and file classificationEvaluate classification models for sentiment prediction of restaurant reviewsWork with clustering models for file type classificationsUse anomaly detection to find anomalies in both network traffic and login historyWork with ASP.NET Core Blazor to create an ML.NET enabled web applicationIntegrate pre-trained TensorFlow and ONNX models in a WPF ML.NET application for image classification and object detectionWho this book is for If you are a .NET developer who wants to implement machine learning models using ML.NET, then this book is for you. This book will also be beneficial for data scientists and machine learning developers who are looking for effective tools to implement various machine learning algorithms. A basic understanding of C# or .NET is mandatory to grasp the concepts covered in this book effectively.

Author: Sudipta Mukherjee
Publisher: Apress
ISBN: 9781484265420
Category : Computers
Languages : en
Pages : 335

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Book Description
Get introduced to ML.NET, a new open source, cross-platform machine learning framework from Microsoft that is intended to democratize machine learning and enable as many developers as possible. Dive in to learn how ML.NET is designed to encapsulate complex algorithms, making it easy to consume them in many application settings without having to think about the internal details. You will learn about the features that do the necessary “plumbing” that is required in a variety of machine learning problems, freeing up your time to focus on your applications. You will understand that while the infrastructure pieces may at first appear to be disconnected and haphazard, they are not. Developers who are curious about trying machine learning, yet are shying away from it due to its perceived complexity, will benefit from this book. This introductory guide will help you make sense of it all and inspire you to try out scenarios and code samples that can be used in many real-world situations. What You Will Learn Create a machine learning model using only the C# language Build confidence in your understanding of machine learning algorithms Painlessly implement algorithms Begin using the ML.NET library software Recognize the many opportunities to utilize ML.NET to your advantage Apply and reuse code samples from the book Utilize the bonus algorithm selection quick references available online Who This Book Is For Developers who want to learn how to use and apply machine learning to enrich their applications

Author: Khalid Saeed
Publisher: Springer
ISBN: 3662452375
Category : Computers
Languages : en
Pages : 718

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Book Description
This book constitutes the proceedings of the 13th IFIP TC 8 International Conference on Computer Information Systems and Industrial Management, CISIM 2014, held in Ho Chi Minh City, Vietnam, in November 2014. The 60 paper presented in this volume were carefully reviewed and selected from 98 submissions. They are organized in topical sections named: algorithms; biometrics and biometrics applications; data analysis and information retrieval; industrial management and other applications; modelling and optimization; networking; pattern recognition and image processing; and various aspects of computer security.

Author: Asra Q. Nomani
Publisher: Bombardier Books
ISBN: 1637580053
Category : Political Science
Languages : en
Pages : 396

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Book Description
From California to the West Bank, former Wall Street Journal reporter Asra Q. Nomani spans the globe, investigating a hidden network of keyboard warriors who hide behind fake identities and pseudonymous Twitter and Facebook accounts. These digital trolls launch virulent attacks against Muslim reformers and others who challenge their divisive attempts to destroy American freedoms. In Woke Army, the author moves from being hunted by this network to being the hunter. The book uncovers the real identities of the network’s members, chronicles their secret operations, and reveals their impact on American public debate, from policing to education in our K–12 schools. In doing so, Nomani uncovers an unholy alliance between radical Muslims, who preach jihad against Western freedoms, and far left activists whose divisive ideology turns all of society’s issues into a race war. The shock troops of this dangerous “red-green alliance” work in tandem, using harassment, threats, and bullying to silence critics, and labeling those who speak out as “Islamophobic” or “racist.” A must-read for anyone who fears for America’s freedoms, Woke Army reveals what can happen when activism, radicalism, and the dark web collide.

Author: Mark J. Price
Publisher: Packt Publishing Ltd
ISBN: 1788471571
Category : Computers
Languages : en
Pages : 819

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Book Description
Publisher's Note: Microsoft stops supporting .NET Core 3.1 in December 2022. The newer 7th edition of this book is available that covers .NET 7 (end-of-life May 2024) or .NET 6 (end-of-life November 2024), with C# 11 and EF Core 7. Key FeaturesBuild modern, cross-platform applications with .NET Core 3.0Get up to speed with C#, and up to date with all the latest features of C# 8.0Start creating professional web applications with ASP.NET Core 3.0Book Description In C# 8.0 and .NET Core 3.0 – Modern Cross-Platform Development, Fourth Edition, expert teacher Mark J. Price gives you everything you need to start programming C# applications. This latest edition uses the popular Visual Studio Code editor to work across all major operating systems. It is fully updated and expanded with new chapters on Content Management Systems (CMS) and machine learning with ML.NET. The book covers all the topics you need. Part 1 teaches the fundamentals of C#, including object-oriented programming, and new C# 8.0 features such as nullable reference types, simplified switch pattern matching, and default interface methods. Part 2 covers the .NET Standard APIs, such as managing and querying data, monitoring and improving performance, working with the filesystem, async streams, serialization, and encryption. Part 3 provides examples of cross-platform applications you can build and deploy, such as web apps using ASP.NET Core or mobile apps using Xamarin.Forms. The book introduces three technologies for building Windows desktop applications including Windows Forms, Windows Presentation Foundation (WPF), and Universal Windows Platform (UWP) apps, as well as web applications, web services, and mobile apps. What you will learnBuild cross-platform applications for Windows, macOS, Linux, iOS, and AndroidExplore application development with C# 8.0 and .NET Core 3.0Explore ASP.NET Core 3.0 and create professional web applicationsLearn object-oriented programming and C# multitaskingQuery and manipulate data using LINQUse Entity Framework Core and work with relational databasesDiscover Windows app development using the Universal Windows Platform and XAMLBuild mobile applications for iOS and Android using Xamarin.FormsWho this book is for Readers with some prior programming experience or with a science, technology, engineering, or mathematics (STEM) background, who want to gain a solid foundation with C# 8.0 and .NET Core 3.0.

Author: Susanne Stoll-Kleemann
Publisher: Springer
ISBN: 9783540369165
Category : Technology & Engineering
Languages : en
Pages : 386

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Book Description
Participatory Processes for Natural Resource Management Ortwin Renn University of Stuttgart, Stuttgart, Germany Need for analytic-deliberative processes Inviting the public to be part of the decision making process in natural resource management has been a major objective in European and American environmental policy arenas. The US-National Academy of Sciences has encouraged environmental protection agencies to foster citizen participation and public involvement for making environmental policy making and natural resource management more effective and democratic (Stern and Fineberg 1996). The report emphasizes the need for a combination of assessment and dialogue which the authors have framed the "analytic-deliberative" approach. Unfortunately, early public involvement of the public in deliberative processes may compromise, however, the objective of efficient and effective policy implementation or violate the principle of fairness (Cross 1998, Okrent 1998). Another problem is that the public consists of many groups with different value structures and preferences. Without a systematic procedure to reach consensus on values and preferences, the public's position often appears as unclear (Coglianese 1997, Rossi 1997). Participatory processes are thus needed that combine technical expertise, rational decision making, and public values and preferences. How can and should natural resource managers collect public preferences, integrate public input into the management process, and assign the appropriate roles to technical experts, stakeholders (i. e.

Author: Irene M. Ong
Publisher:
ISBN:
Category :
Languages : en
Pages : 144

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Book Description

Author: Bamshad Mobasher
Publisher: Springer Science & Business Media
ISBN: 3540298460
Category : Computers
Languages : en
Pages : 332

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Book Description
This book constitutes the thoroughly refereed post-proceedings of the Second Workshop on Intelligent Techniques in Web Personalization, ITWP 2003, held in Acapulco, Mexico in August 2003 as part of IJCAI 2003, the 18th International Joint Conference on Artificial Intelligence. The 17 revised full papers presented were carefully selected and include extended versions of some of the papers presented at the ITWP 2003 workshop as well as a number of invited chapters by leading researchers in the field of Intelligent Techniques for Web Personalization. The papers are organized in topical sections on user modelling, recommender systems, enabling technologies, personalized information access, and systems and applications.

Author: A. G. Cohn
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 856

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Book Description
A collection of refereed papers presented at the 11th European Conference on Artificial Intelligence held in Amsterdam, The Netherlands in August 1994.

Author: Ian H. Witten
Publisher: Elsevier
ISBN: 008047702X
Category : Computers
Languages : en
Pages : 558

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Book Description
Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; and much more. This text is designed for information systems practitioners, programmers, consultants, developers, information technology managers, specification writers as well as professors and students of graduate-level data mining and machine learning courses. - Algorithmic methods at the heart of successful data mining—including tried and true techniques as well as leading edge methods - Performance improvement techniques that work by transforming the input or output