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Feature Engineering
Machine learning is only as good as its training data. Learn how to process data properly before training your models.
Includes Python, Machine Learning, Algorithms, Datasets, Feature Selection, Dimensionality Reduction, Engineering, Data Transformation, and more.
Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary6 hoursCertificate of completion
YesPrerequisites
3 coursesWe suggest you complete the following courses before you get started with Feature Engineering:- Linear Algebra
- Getting Started with Python for Data Science
- Python for Data Science: Working with Data
About this skill path
A machine learning model is only as good as the data it learns from. Feature Engineering helps ensure data quality by scaling, normalizing, and transforming raw data before using it in a machine learning model. In this Skill Path, you will learn to safeguard data quality, turn attributes into features, and verify that your data meets the assumptions of the model you want to train.
Skills you'll gain
- Turn raw data into features
- Select the right features for a model
- Implement principal component analysis
Syllabus
4 units • 4 lessons • 4 projects • 3 quizzes- 1
Introduction to Feature Engineering
Find out what you’ll learn in the feature engineering skill path!
- 2
Transforming Data into Features
Learn about different methods of transforming data into features.
- 3
Feature Selection Methods
Learn about different feature selection methods and their implementations in Python!
- 4
Feature Engineering by Reducing Dimensionality
Learn feature engineering methods that reduce the dimensionality of a dataset.
Projects in this skill path
- Project
Transforming Data into Features
Perform data transformations on a clothing company customer review dataset! - Project
Wrapper Methods
Implement wrapper methods on a dataset relating to health and eating habits! - Project
Predict Wine Quality with Regularization
Build a wine quality classifier with logistic regression using regularization.
Reviews from learners
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Related resources
- Article
Feature Importance
Learn about feature importance and how to calculate it. - Article
Principal Component Analysis
An introduction to principal component analysis (PCA) and example implementation in Python - Article
The Machine Learning Process
Learn the general structure of how to approach Machine Learning problems in a methodical way.
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What's included in skill paths
Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.