This course was created with the
course builder. Create your online course today.
Start now
Create your course
with
Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Data treatment before Modelling
Introduction to Data Treatment
Understanding the importance of data treatment before modeling
Overview of the data treatment process
Common challenges in preparing data for modeling
Data Cleaning Techniques
Handling missing data
Outlier detection and treatment techniques
Feature scaling and normalization
Dealing with categorical variables
Data Preprocessing
Exploratory Data Analysis (EDA) for feature selection
Handling imbalanced datasets
Dimensionality reduction techniques
Data transformation methods
Data Splitting and Validation
Importance of data splitting for modeling
Techniques for cross-validation
Strategies for selecting training and testing datasets
Conclusion
Best practices for data treatment before modeling
Resources for further learning and practice
Outlier detection and treatment techniques
Lesson content locked
If you're already enrolled,
you'll need to login
.
Enroll in Course to Unlock