Using ML.NET to Build Machine Learning Models/

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Challenge: Analyzing Clustered Data

Test yourself by making a clustering machine learning task meaningful.

We'll cover the following...

Problem statement

Using the coding playground at the end of this lesson, perform the tasks highlighted in the “Problem statement” section.

Problem statement

In the playground below, we have a full end-to-end process of training and using a clustering model against housing market data. We tell the model to create three distinct clusters and then feed the data to it.

Once the model is trained, we pass an example of a house to it to predict what cluster it would belong in and print this information in the console. We also print distance measures. We then print the distributions of the training data ...

Introduction to ML.NET

Machine Learning Fundamentals

Selecting a Problem for Machine Learning

Built-In Supervised Learning Tasks in ML.NET

Built-In Unsupervised Learning Tasks in ML.NET

Deep Learning and Neural Networks

Automating Machine Learning Tasks with AutoML

Saving and Consuming Machine Learning Models

Building an Image Analysis Application

Wrapping Up

Implementation of U-Net for Image Segmentation

Appendix

Challenge: Analyzing Clustered Data

Problem statement