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Introduction to Machine Learning

Introduction to Machine Learning

This repository contains all course assignments of my Introduction to Machine Learning course and will get you up to speed with Microsoft's new ML.NET library.

By working through the code examples, you will learn how to design, train, and evaluate complex AI models with simple C# code. I'll provide you with all the code, libraries, and data sets you need to get started.

Please note that this repository only contains code examples with no additional support.

If you prefer a full-featured e-learning experience with live coaching, please check out my online course here:

https://www.machinelearningadvantage.com/introduction-to-machinelearning

Table of contents

Regression: Predict house prices in California

Regression: Predict taxi fares in New York

Binary classification: Predict heart disease in Ohio

Multiclass classification: Recognize handwriting

Evaluating models: Detect SMS spam messages

Decision trees: Predict Titanic survivors

Ensembles: Predict bike demand in Washington DC

Clustering: Classify Iris flowers

Recommendation: Build a movie recommender

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