Auto-Scikit-Learn is a Python library for automating the process of model selection and hyperparameter tuning using scikit-learn. The library allows users to easily and
efficiently find the best model and hyperparameters for their data without requiring any prior knowledge or experience in machine learning.
Features:
1.Automated model selection
2.Automated hyperparameter tuning
3.Simple API for easy implementation
4.Optimized for speed and efficiency
5.Compatible with scikit-learn and pandas
How it works:
Auto-Scikit-Learn uses Bayesian optimization to search for the best model and hyperparameters for a given dataset. The library takes as input a dataset and a list of
models and their associated hyperparameters to search over. It then iteratively trains and evaluates models using cross-validation, and selects the best performing model
and hyperparameters.
Technologies Used:
1.Python
2.Scikit-learn
3.Pandas
4.Hyperopt
5.Joblib