Feature Engineering
This course helps students to identify the most impactful features for your model. It will build upon foundational machine learning techniques to hone predictive skills and discover critical danger points in patterns. By the end of this course, students will be able to determine key features in models.
4 hours of instruction
This course helps students to identify the most impactful features for your model. It will build upon foundational machine learning techniques to hone predictive skills and discover critical danger points in patterns. By the end of this course, students will be able to determine key features in models.
OBJECTIVES
- Define use cases for feature engineering
- Identify and evaluate the most impactful numerical and categorical variables
PREREQUISITES
Introduction to Clustering in Python
SYLLABUS & TOPICS COVERED
- Feature Engineering
- Feature engineering definition and use cases
- Feature engineering on different types of data
- Implement feature engineering techniques on numeric, categorical, temporal, and spatial data
SOFTWARE REQUIREMENTS
You will have access to a Python-based JupyterHub environment for this course. No additional download or installation is required.
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