Machine Learning
3243 learners
Feature Engineering for Machine Learning
Explore feature engineering using UCI's Abalone Dataset in this course. Enhance your skills in feature extraction, selection, and transformation to boost machine learning model performance. Learn to craft valuable features, apply different selection strategies, and use feature combinations to uncover data patterns.
Python
Scikit-learn
6 lessons
21 practices
3 hours
Feature Engineering
Lessons and practices
Display Dataset Features
Display Dataset Descriptive Features
Display More Dataset Entries
Implementing Median Imputation for Numeric Features
Applying Label Encoding to Categorical Data
Debugging the Feature Engineering Pipeline
Applying Categorical Encoding and Median Imputation on the Abalone Dataset
Calculating the Area
Volume As a Feature?
What's Their Density?
Calculate Relative Height
Playing With Wrapper Method
Implementing Embedded Feature Selection Method using Lasso
Refining Feature Selection with f_classif
Create a New Feature by Multiplying Length and Diameter
Debugging Feature Combinations Analysis Code
Exploring New Feature Combinations in Abalone Dataset
Assessing the Impact of the 'Viscera_Shell' Feature on Model Performance
Alter the Linear Regression Model for a Different Feature Combination
Debugging 'Viscera_Shell' Feature
Effect on Model Performance by Engineering a New Feature
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