About This Course

This course is for you if you want to have a real feel of the machine learning techniques without having to learn all the complicated math. Additionally, this course is also for you if you have had previous hours and hours of machine learning theory but could never got a change or figure out how to implement and solve data science problems with it.

The approach in this course is very practical and we will start everything from scratch. We will immediately start coding after a couple of introductory tutorials and we try to keep the theory to bare minimal. 

Below is a brief outline of this course.

Segment 1: Introduction To Course And Say Hi To MATLAB

Segment 2: Data Preprocessing

Segment 3: Classification Algorithms In MATLAB

Segment 4: Clustering Algorithms In MATLAB

Segment 5: Dimensionality Reduction

Segment 6: Project: Malware Analysis

All the coding will be done in MATLAB which is one of the fundamental programming languages for engineering and science students and is frequently used by top data science research groups worldwide.

Our Promise to You

By the end of this course, you will have learned about machine learning using MATLAB.

30 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today and learn more about the machine learning using MATLAB.

Course Curriculum

Section 1 - Introduction To Course And MATLAB
Downloadable Material 00:00:00
Course Introduction 00:00:00
MATLAB Essentials For The Course 00:00:00
Section 2 - Data Preprocessing
Section Introduction 00:00:00
Importing The Dataset 00:00:00
Removing Missing Data – Part 1 00:00:00
Removing Missing Data – Part 2 00:00:00
Feature Scaling 00:00:00
Handling Outliers – Part 1 00:00:00
Handling Outliers – Part 2 00:00:00
Dealing With Categorical Data – Part 1 00:00:00
Dealing With Categorical Data – Part 2 00:00:00
Your Preprocessing Template 00:00:00
Section 3 - K - Nearest Neighbor
K – Nearest Neighbor Intuition 00:00:00
K – Nearest Neighbor In MATLAB – Part 1 00:00:00
K – Nearest Neighbor In MATLAB – Part 2 00:00:00
Visualizing The Decision Boundaries Of K – Nearest Neighbor 00:00:00
Explaining The Code For Visualization 00:00:00
Here Is Our Classification Template 00:00:00
How To Change Default Options And Customize Classifiers 00:00:00
Customization Options For K – Nearest Neighbor 00:00:00
Section 4 - Naive Bayes
Naive Bayesain Intuition – Part 1 00:00:00
Naive Bayesain Intuition – Part 2 00:00:00
Naive Bayesain In MATLAB 00:00:00
Customization Options For Naive Bayesain 00:00:00
Section 5 - Decision Trees
Decision Trees Intuition 00:00:00
Decision Trees In MATLAB 00:00:00
Visualizing Decision Trees Using The View Function 00:00:00
Customization Options For Decision Trees 00:00:00
Section 6 - Support Vector Machines
Support Vector Machines Intuition 00:00:00
Kernel Support Vector Machines Intuition 00:00:00
Support Vector Machines In MATLAB 00:00:00
Customization Options For Support Vector Machines 00:00:00
Section 7 - Discriminant Analysis
Discriminant Analysis Intuition 00:00:00
Discriminant Analysis In MATLAB 00:00:00
Customization Options For Discriminant Analysis 00:00:00
Section 8 - Ensembles
Ensembles Intuition 00:00:00
Ensembles In MATLAB 00:00:00
Customization Options For Ensembles 00:00:00
Section 9 - Performance Evaluation
Evaluating Classifiers: Confusion Matrix (Theory) 00:00:00
Validation Methods (Theory) 00:00:00
Validation Methods In MATLAB – Part 1 00:00:00
Validation Methods In MATLAB – Part 2 00:00:00
Evaluating Classifiers In MATLAB 00:00:00
Section 10 - K-Means
K-Means Clustering Intuition 00:00:00
Choosing The Number Of Clusters 00:00:00
K-Means In MATLAB – Part 1 00:00:00
K-Means In MATLAB – Part 2 00:00:00
Section 11 - Hierarchical Clustering
Hierarchical Clustering Intuition – Part 1 00:00:00
Hierarchical Clustering Intuition – Part 2 00:00:00
Hierarchical Clustering In MATLAB 00:00:00
Section 12 - Dimensionality Reduction
Principal Component Analysis 00:00:00
Principal Component Analysis In MATLAB – Part 1 00:00:00
Principal Component Analysis In MATLAB – Part 2 00:00:00
Section 13 - Project: Malware Analysis
Problem Description 00:00:00
Customizing Code Templates For Completing Task 1 And 2 – Part 1 00:00:00
Customizing Code Templates For Completing Task 1 And 2 – Part 2 00:00:00
Customizing Code Templates For Completing Task 3, Task 4, And 5 00:00:00
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