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A course for researchers familiar with Python, introducing the fundamentals of machine learning with Scikit-Learn. Pre-Alpha This lesson is in the pre-alpha phase, which means that it is in early development, but has not yet been taught.

    A course for researchers familiar with Python, introducing the fundamentals of machine learning with Scikit-Learn.
    Introduction to Machine Learning in Python
    • Introduction to Machine Learning in Python
    • Key Points
    • Instructor Notes
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    Introduction to Machine Learning in Python
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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
    • Extract All Images

    • Reference

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    Instructor Notes

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    Introduction


    Supervised methods - Regression


    Supervised methods - classification


    Ensemble Methods


    Unsupervised methods - Clustering


    Unsupervised methods - Dimensionality reduction


    Neural Networks


    Ethics and the Implications of Machine Learning


    Find out more



    This lesson is subject to the Code of Conduct

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