ML.NET revealed : simple tools for applying machine learning to your applications / Sudipta Mukherjee.
2021
Q325.5
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Details
Title
ML.NET revealed : simple tools for applying machine learning to your applications / Sudipta Mukherjee.
Author
Mukherjee, Sudipta.
ISBN
9781484265437 (electronic bk.)
1484265432 (electronic bk.)
1484265440
9781484265444
1484265424
9781484265420
9781484265444 (print)
1484265432 (electronic bk.)
1484265440
9781484265444
1484265424
9781484265420
9781484265444 (print)
Publication Details
Berkeley, CA : Apress, 2021.
Language
English
Description
1 online resource (185 pages)
Item Number
10.1007/978-1-4842-6543-7 doi
Call Number
Q325.5
Dewey Decimal Classification
006.3/1
004.165
004.165
Summary
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 This book is for developers who want to learn how to use and apply machine learning to enrich their applications. Sudipta Mukherjee is an electronics engineer by education and a computer scientist by profession. He holds a degree in electronics and communication engineering. He is passionate about data structure, algorithms, text processing, natural language processing tools development, programming languages, and machine learning. He is the author of several technical books. He has presented at @FuConf and other developer events, and he lives in Bangalore with his wife and son
Note
Includes index.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Description based on print version record.
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ML. NET Revealed : Simple Tools for Applying Machine Learning to Your Applications.
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Table of Contents
Chapter 1: Meet ML.NET
Chapter 2: The Pipeline
Chapter 3: Handling Data
Chapter 4: Regressions
Chapter 5: Classifications
Chapter 6: Clustering
Chapter 7: Sentiment Analysis
Chapter 8: Product Recommendation
Chapter 9: Anomaly Detection
Chapter 10: Object Detection.
Chapter 2: The Pipeline
Chapter 3: Handling Data
Chapter 4: Regressions
Chapter 5: Classifications
Chapter 6: Clustering
Chapter 7: Sentiment Analysis
Chapter 8: Product Recommendation
Chapter 9: Anomaly Detection
Chapter 10: Object Detection.