These series of articles will introduce you to the world of Machine Learning via Microsoft’s open source, cross-platform framework ML.NET
1. Introduction
This article introduces you to the ML.NET framework and gives a very brief
overview of Machine Learning tasks that are possible to do with ML.NET.
2. Model Builder
Create a very simple Cat Vs Dog Classifier by using the Model Builder Tool.
3. ML.NET Pipeline
This articles demonstrates the Machine Learning pipeline. We also examine what kind of Machine Learning tasks ML.NET currently supports.
4. How to load data with ML.NET
Machine Learning Data comes in all shapes and sizes. Learn how to load, filter and save data using ML.NET
5. Transform data
Data Transformation is one of the most important steps in building ML.NET Model. This article will demonstrate how a messy and chaotic data can be put in order using the Transformation Functions ML.NET provides.
6. Train ML.NET Model
This article demonstrates how to Train ML.NET Model. Learn how to create and append a trainer to a machine learning pipeline. Create a small demo to solve the Bike Rental Problem using Regression.
7. How to Preprocess Data in ML.NET
Learn how to properly use the data transformation techniques. Explore different scenarios, data types and how to handle them accordingly.