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An open source python framework for automated feature engineering
Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.
Predict what a customer will buy next based on purchase history using automated feature engineering
Predict whether a student will correctly answer a problem based on past performance using automated feature engineering
Predict remaining useful life of a component based on historical sensor observations using automated feature engineering
A general-purpose framework for solving problems with machine learning applied to predicting customer churn
Predict how many medals a country will win at the Olympics based on past performance using automated feature engineering
Predict the poverty of households in Costa Rica using automated feature engineering.
Predict whether or not a patient will show up to their next appointment using automated feature engineering
Predict taxi trip duration based on historical trips using automated feature engineering
Predict whether internet traffic is malicious given historical router traffic data
Predict whether a loan will be repaid using automated feature engineering.
Use docker to provision Featuretools with a Jupyter notebook server
Deep learning for time-varying multi-entity datasets
Hands on tutorials demonstrating the concepts of Prediction engineering, Feature engineering and automation in data science.
Convert D3M raw dataset to D3M clean dataset with Featuretools