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AI and machine learning are no longer the technology of the future: they’re forever ingrained in every industry. But algorithms are only as good as their data, making Feature Engineering essential. We’ve launched a new Feature Engineering course that will provide an opportunity to work hands-on through a complete feature development process, including:
- Discover which features in a dataset are likely to be the most useful
- Learn to create the the right kind of features for your particular model
- Assess whether new features help or harm performance
In the new course, you’ll learn a variety of feature engineering techniques to improve your own machine learning projects
Lessons
1 ) What Is Feature Engineering
Learn the steps and principles of creating better features
2 ) Mutual Information
Locate features with the most potential.
3 ) Creating Features
Transform features with Pandas to suit your model.
4 ) Clustering With K-Means
Untangle complex spatial relationships with cluster labels.
5 ) Principal Component Analysis
Discover new features by analyzing variation.
6 ) Target Encoding
Boost any categorical feature with this powerful technique.
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