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Data Science with F# and ML.NET

Data Science with C# and ML.NET

This repository contains all course assignments of my Data Science with F# and ML.NET 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 F# 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/datascience-with-fsharp

Table of contents

Transforming data: Processing California housing data

Regression: Predict taxi fares in New York

Case study: Predict house prices in Iowa

Binary classification: Predict heart disease in Ohio

Case study: Detect credit card fraud in Europe

Multiclass classification: Recognize handwriting

Evaluating models: Detect SMS spam messages

Case study: Flag toxic comments on Wikipedia

Decision trees: Predict Titanic survivors

Case study: Predict Diabetes in Pima indians

Ensembles: Predict bike demand in Washington DC

Clustering: Classify Iris flowers

Recommendation: Build a movie recommender