Machine Learning Foundations

Classifications / Machine Learning / Machine Learning Foundations

TRACK

Core supervised learning concepts, model families, and evaluation basics.

16 lessons

LESSONS

1. 001
   Machine Learning Fundamentals

   30 min

   [TODO]
2. 002
   Linear Regression Fundamentals

   30 min

   [TODO]
3. 003
   Gradient Descent Fundamentals

   30 min

   [TODO]
4. 004
   Polynomial Features and Regularization

   30 min

   [TODO]
5. 005
   Logistic Regression Fundamentals

   30 min

   [TODO]
6. 006
   Decision Trees and Rule-Based Splits

   30 min

   [TODO]
7. 007
   Naive Bayes for Text Classification

   30 min

   [TODO]
8. 008
   Classification Metrics and Trade-Offs

   30 min

   [TODO]
9. 009
   Support Vector Machines and Margin

   30 min

   [TODO]
10. 010
    K-Nearest Neighbors and Similarity

    30 min

    [TODO]
11. 011
    Random Forest and Bagging

    30 min

    [TODO]
12. 012
    Gradient Boosting and Sequential Correction

    30 min

    [TODO]
13. 013
    Feature Engineering and Representation

    30 min

    [TODO]
14. 014
    Cross-Validation and Reliable Evaluation

    30 min

    [TODO]
15. 015
    Overfitting, Underfitting, and Regularization

    30 min

    [TODO]
16. 016
    Learning Curves and Model Diagnosis

    30 min

    [TODO]

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