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Beginner-friendly introduction to machine learning in Python using scikit-learn. Beta This lesson is in the beta phase, which means that it is ready for teaching by instructors outside of the original author team.

    Beginner-friendly introduction to machine learning in Python using scikit-learn.
    Introduction to Machine Learning with Scikit-Learn
    • Introduction to Machine Learning with Scikit-Learn
    • Key Points
    • Instructor Notes
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    Introduction to Machine Learning with Scikit-Learn
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    Summary and Schedule
    1. Introduction
    2. Supervised methods - Regression
    3. Supervised methods - Classification
    4. Ensemble methods
    5. Unsupervised methods - Clustering
    6. Unsupervised methods - Dimensionality reduction
    7. Neural Networks
    8. Ethics and the Implications of Machine Learning
    9. Find out more

    • Key Points
    • Instructor Notes
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    Instructor Notes

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    IntroductionWhat is machine learning?Getting started with Scikit-LearnWhat will we cover today?


    Supervised methods - RegressionSupervised learningRegression


    Supervised methods - ClassificationClassification


    Ensemble methodsEnsemble methods


    Unsupervised methods - ClusteringUnsupervised learningClustering


    Unsupervised methods - Dimensionality reductionDimensionality reductionDimensionality reduction with Scikit-Learn


    Neural NetworksNeural networks


    Ethics and the Implications of Machine LearningEthics and machine learningEthics of machine learning in research


    Find out moreOther algorithms



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