solegalli/feature-selection-for-machine-learning
Code repository for the online course Feature Selection for Machine Learning
This project helps data scientists and machine learning engineers refine their datasets by identifying and removing irrelevant or redundant features. It takes raw datasets with many variables and outputs a more focused dataset, ready for building more efficient and accurate predictive models. The end-user is a data practitioner looking to improve model performance and interpretability.
343 stars. No commits in the last 6 months.
Use this if you are a data scientist or machine learning engineer struggling with high-dimensional datasets that lead to slow model training or poor prediction accuracy.
Not ideal if you are looking for a fully automated, black-box solution without understanding the underlying feature selection techniques.
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Oct 31, 2024
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