Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Machine Learning for Data Science using MATLAB!
Introduction to the Course and MATLAB
Introduction to the course (5:10)
MATLAB essentials for the course (8:26)
Data Preprocessing
Source Code and Data
Section introduction (1:54)
Importing the data into MATLAB (7:25)
Handling missing data (part 1) (7:43)
Handling missing data (part 2) (6:46)
Feature scaling (9:50)
Handling outliers (part 1) (9:07)
Handling outliers (part 2) (6:02)
Dealing with categorical data (part 1) (9:50)
Dealing with categorical data (part 2) (6:20)
Your data preprocessing template (3:58)
Classification
Source Code and Data
K-Nearest Neighbor
KNN intuition (7:27)
KNN in MATLAB (part 1) (10:13)
KNN in MATLAB (part 2) (12:38)
Visualizing the decision boundaries of KNN (13:06)
Explaining the code for visualization (9:53)
Here is our classification template (4:21)
Customization options (part 1) (7:19)
Customization options (part 2) (10:32)
Naive Bayes
Naive Bayesian intuition (part 1) (11:24)
Naive Bayesian intuition (part 2) (15:00)
Naive Bayesian in MATLAB (6:06)
Customization options for Naive Bayesian In MATLAB (4:18)
Decision Trees
Decision trees intuition (10:24)
Decision trees in MATLAB (4:48)
Visualizing the decision tree using the view function (9:02)
Customization options for decision trees (9:20)
Support Vector Machines
SVM intuition (15:21)
Kernel SVM intuition (6:45)
SVM in MATLAB (6:37)
Customization options for SVM (9:30)
Discriminant Analysis
Discriminant analysis intuition (13:12)
Discriminant analysis in MATLAB (4:01)
Customization options for discriminant analysis (5:03)
Ensembles
Ensembles intuition (14:15)
Ensembles in MATLAB (8:53)
Customization options for ensembles (13:02)
Performance Evaluation
Evaluating classifiers: confusion matrix (theory) (15:51)
Validation methods (theory) (12:04)
Validation methods (part 1) (12:08)
Validation methods (part 2) (8:32)
Evaluating classifiers in MATLAB (8:22)
Clustering
Source Code and Data
K-Means
K-means clustering intuition (12:04)
Choosing the number of clusters (14:19)
K-means clustering in MATLAB (part 1) (12:55)
K-means clustering in MATLAB (part 2) (16:27)
Hierarchical Clustering
Hierarchical clustering intuition (part 1) (9:41)
Hierarchical clustering intuition (part 2) (15:38)
Hierarchical clustering in MATLAB (19:25)
Dimensionality Reduction
Source Code and Data
Principal component analysis (7:40)
PCA in MATLAB (part 1) (13:41)
PCA in MATLAB (part 2) (17:00)
Project: Malware Analysis
Source Code and Data
Customizing code templates for completing task 1 and 2 (part 2) (5:30)
Project description (8:17)
Customizing code templates for completing task 1 and 2 (part 1) (9:40)
Customizing code templates for completing task 3, 4 and 5 (17:59)
Teach online with
KNN intuition
Lesson content locked
If you're already enrolled,
you'll need to login
.
Enroll in Course to Unlock