Course curriculum

    1. Introduction to course

    2. Introduction to MATLAB

    1. Section introduction

    2. Importing the data into MATLAB

    3. Handling missing data (part 1)

    4. Handling missing data (part 2)

    5. Feature scaling

    6. Outliers (part 1)

    7. Outliers (part 2)

    8. Dealing with categorical data (part 1)

    9. Dealing with categorical data (part 2)

    10. Your data preprocessing template

    1. KNN intuition

    2. KNN in MATLAB (part 1)

    3. KNN in MATLAB (part 2)

    4. Visualizing the decision boundaries of KNN

    5. Explaining the code of visualization

    6. Here is our classification template

    7. Customization options (part 1)

    8. Customization options (part 2)

    1. Intuition of Naive Bayesain (part 1)

    2. Intuition of Naive Bayesian (part 2)

    3. Naive Bayesian in Matlab

    4. Customization options of Naive Bayesian In MATLAB

    1. Decision trees intuition

    2. Decision tree in MATLAB

    3. Visualizing the decision tree using the view function

    4. Customization options for decision trees

    1. SVM intuition (part 1)

    2. Kernel SVM intuition

    3. SVM in MATLAB

    4. Customization options for SVM

About this course

  • $9.99
  • 57 lessons
  • 9.5 hours of video content

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