index.md

@def title = "Data Science Tutorials in Julia" Tutorials for learning data science using Julia, with a focus on machine learning (ML) using the MLJ toolbox and related packages.

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How to Run Code ►

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What kind of user are you? These are our recommendations for different types of users:

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@@get-started-tab,selected New to Julia? @@

@@get-started-tab New to ML? @@

@@get-started-tab New to Julia and ML? @@

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Completely new to Julia?

Try one of these external resources:

• Julia's learning resources page

• Learn X in Y minutes

• HelloJulia

Machine Learning expert with beginner-level Julia?

We suggest you start with this tutorial:

• Telco Churn (MLJ for Data Scientists in Two Hours), intermediate, classification, one-hot, ROC curves, confusion matrices, feature importance, feature selection, controlling iteration, tree booster, hyper-parameter optimization (tuning)

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New to machine learning but have moderate Julia skills?

Start out with the Introduction to Statistical Learning tutorials, or one of these external resources:

• MLCourse: Teaching material for an introductory machine learning course at EPFL (for an interactive preview see here).

• Julia Data Science: Book focused on exploratory data analysis with less on ML. @@

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New to both Julia and machine learning?

To get started with Julia, you can try one of the external resources found in the New to Julia tab.

Once you have basic Julia competency, try the Introduction to Statistical Learning tutorials or one of these external resources:

• Julia Data Science: Book focused on exploratory data analysis with less on ML.

• MLCourse: Teaching material for an introductory machine learning course at EPFL (for an interactive preview see here). @@ @@