Data Preprocessing for Machine Learning using MATLAB

This course is for you if you want to fully equip yourself with the art of applied machine learning using MATLAB. This course is also for you if you want to apply the most commonly used data preprocessing techniques without having to learn all the complicated maths. Additionally, this course is also for you if you have had previous hours and hours of machine learning implementation but could never figure out how to further improve the performance of the machine learning algorithms. By the end of this course, you will have at your fingertips, a vast variety of most commonly used data preprocessing techniques that you can use instantly to maximize your insight into your data set. 

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 a bare minimum. 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.

Course Outline:

• Segment 1: Introduction to the course and MATLAB.
• Segment 2: Handling Missing Values.
• Segment 3: Dealing with Categorical Variables.
• Segment 4: Outlier Detection.
• Segment 5: Feature Scaling and Data Discretization.
• Segment 6: Project: Selecting Techniques for your Dataset.

Your Benefits and Advantages: 

• If you do not find the course useful, you are covered with a 30-day money-back guarantee, a full refund, no questions asked!

• You will be sure of receiving quality content since the instructors have already many courses in MATLAB on TutorialsPoint. 

• You have lifetime access to the course.

• You have instant and free access to any updates I add to the course.

• You have access to all Questions and discussions initiated by other students.

• You will receive my support regarding any issues related to the course.

• Check out the curriculum and Freely available lectures for a quick insight.

Who this course is for?

• Students, Entrepreneurs, Researchers, Instructors, Engineers, Programmers, Simulators.
• Anyone who wants to analyze the data.