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Machine Learning for Data Science using MATLAB
First Section
1 - Introduction to course (5:10)
2 - Introduction to matlab (8:26)
--------------------------- Data Preprocessing ---------------------------
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)
Outliers (Part 1) (9:07)
Outliers (Part 2) (6:02)
Dealing with Categorical Data (Part 1) (9:50)
Dealing with Categorical Data (Part 2) (6:20)
Your Data Preproprocessing Timplate (3:58)
--------------------------- Classification ---------------------------
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 of visualization (9:53)
Here is our classification template (4:21)
Customization options (part 1) (7:19)
Customization options (part 2) (10:32)
Naive Bayes
Intuition of Naive Bayesain (Part 1) (11:24)
Intuition of Naive Bayesain (Part 2) (15:00)
Naive Bayesain in Matlab (6:06)
Customization Options of Naive Bayesain In MATLAB (4:18)
Decision Trees
Decision Trees Intuition (10:24)
Decision tree 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 (Part 1) (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
Confusion Matrix (15:51)
Validation_methods (12:04)
Validation methods (Part 1) (12:08)
Validation methods (Part2) (8:32)
Evaluation (8:22)
-------------------------- Clustering ---------------------------
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)
HC in matlab (19:25)
-------------------------- Dimensionality Reduction ------------------
Code and Data
PCA Intuition (7:40)
PCA in MATLAB (Part 1) (13:41)
PCA in MATLAB (Part 2) (17:00)
Project: Malware Analysis
Project Discription (8:17)
Customizing code templates for completing Task 1 and 2 (Part 1) (9:40)
Customizing code templates for completing Task 1 and 2 (Part 2) (5:30)
Customizing code templates for completing Task 3, 4 and 5 (17:59)
Project Code and Data
Visualizing the Decision Boundaries of KNN
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