Data
38 learners
Feature Selection, Reduction and Streamlining
Identify impactful features, reduce dimensionality, and streamline datasets for analysis. Learn techniques to enhance model efficiency and performance by focusing on the most relevant data attributes.
Pandas
Python
Scikit-learn
5 lessons
21 practices
1 hour
Data Ingestion and Extraction
Lessons and practices
Fill Missing Values in Titanic
Drop Column With Excessive Missing Values
Encode Categorical Data Efficiently
Confirm Your Data Preparation Steps
Defining Features and Target Variable
Adjusting Feature Selection Parameters
Explore Mutual Information for Feature Selection
Selecting Top Features with Chi Square
Evaluate Feature Significance with Chi-Square
Adjusting Random Forest Parameters
Debug Feature Ranking Code
Train and Rank Features
Feature Importance with Random Forests
Explained Variance with PCA Analysis
Exploring PCA Without Scaling
Enhance Your PCA Skills
Creating a DataFrame with PCA
Build a Pipeline in Python
Accessing PCA Explained Variance
Fix the Pipeline Missing Step
Enhance Pipelines with SelectKBest
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