Simple Tools for Applying Machine Learning to Your ApplicationsPaperback Engels 2020 9781484265420
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
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Chapter 02: The Pipeline
Chapter 03: Handling Data
Chapter 04: Regressions
Chapter 05: Classifications
Chapter 06: Clustering
Chapter 07: Sentiment Analysis
Chapter 08: Product Recommendation
Chapter 09: Anomaly Detection
Chapter 10: Object Detection
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