Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Data Preprocessing for Machine Learning using MATLAB
Introduction to course and MATLAB
1 - Intorduction to Course
2 - Introduction to matlab
3 - Importing the dataset into MATLAB
Handling Missing Values
Code and Data
1 - Deletion Strategies
2 - Using mean and mode
3 - Adding_Special_Value
4 - class_specific_mode_mean
5 - Random_Value_Imputation
Dealing with Categorical Variables
Code and Data
2 - Categorical data with order
1 - Categorical data with no order
3 - Frequency_encoding
4 - Target_based_Encoding
Outlier Detection
Code and Data
1 - 3 sigma rule with deletion strategy
2 - 3 sigma rule with filling strategy
3 - Histograms for outliers
4 - Box Plots (Part 1)
5 - Box Plots (Part 2
6 - LOF (Part 1)
7 - LOF (Part 2)
8 - Outliers in categorical variables
Feature Scaling and Data Discretization
Code and Data
1 - Feature Scalling
2 - Equal Width Binning
3 - Equal Frequency Binning
Project: Selecting the Right Method for your Data
Code and Data
Selecting the right method (Part 1)
Selecting the right method (Part 2)
Selecting the right method (Part 2)
Lesson content locked
If you're already enrolled,
you'll need to login
.
Enroll in Course to Unlock