Feature Engineering for Machine Learning

Journey into Machine Learning with Sklearn and TensorflowFeature 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.

Lessons and practices

Lesson 1: Exploring Feature Engineering with the UCI Abalone Dataset

Display Dataset Features

Display Dataset Descriptive Features

Display More Dataset Entries

Lesson 2: Navigating Practical Challenges in Feature Engineering

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

Lesson 3: Unlocking the Secrets of Feature Extraction with the Abalone Dataset

Calculating the Area