Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Machine Learning with ML.NET

You're reading from   Hands-On Machine Learning with ML.NET Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#

Arrow left icon
Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789801781
Length 296 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Jarred Capellman Jarred Capellman
Author Profile Icon Jarred Capellman
Jarred Capellman
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1: Fundamentals of Machine Learning and ML.NET
2. Getting Started with Machine Learning and ML.NET FREE CHAPTER 3. Setting Up the ML.NET Environment 4. Section 2: ML.NET Models
5. Regression Model 6. Classification Model 7. Clustering Model 8. Anomaly Detection Model 9. Matrix Factorization Model 10. Section 3: Real-World Integrations with ML.NET
11. Using ML.NET with .NET Core and Forecasting 12. Using ML.NET with ASP.NET Core 13. Using ML.NET with UWP 14. Section 4: Extending ML.NET
15. Training and Building Production Models 16. Using TensorFlow with ML.NET 17. Using ONNX with ML.NET 18. Other Books You May Enjoy

Summary

Over the course of this chapter, we have deep dived into what goes into a production-ready Windows 10 UWP application architecture, using the work performed in previous chapters as a foundation. We also created a brand new web-page-classification Windows 10 application, utilizing the SdcaLogisticRegression algorithm from ML.NET. Lastly, we also discussed some ways to further enhance the example application (and production applications in general).

With the conclusion of this chapter, this ends the real-world application section. The next section of the book includes both general machine learning practices in an agile production team and extending ML.NET with TensorFlow and Open Neural Network Exchange (ONNX) models. In the next chapter, we will focus on the former.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image