Using ML.NET to Build Machine Learning Models

Solution Review: Improving Model Accuracy

Explore techniques to improve your machine learning model's accuracy in ML.NET by using more comprehensive datasets and adjusting training time. Learn how these changes impact micro and macro accuracies, helping you build more reliable models.

We'll cover the following...

Solving the challenge

1.Introduction to ML.NET

2.Machine Learning Fundamentals

3.Selecting a Problem for Machine Learning

4.Built-In Supervised Learning Tasks in ML.NET

5.Built-In Unsupervised Learning Tasks in ML.NET

6.Deep Learning and Neural Networks

7.Automating Machine Learning Tasks with AutoML

8.Saving and Consuming Machine Learning Models

Mini Project

9.Wrapping Up

Project

10.Appendix

Solution Review: Improving Model Accuracy