AMPL: The ATOM Modeling PipeLine (AMPL) is an open-source, modular, extensible software pipeline for building and sharing models to advance in silico drug discovery, extending the functionality of DeepChem and supporting an array of machine learning and molecular featurization tools.
CHVS: This repository contains Python code for model evaluation in regression tasks, exploring various regression models and helping select the best-performing model for your dataset using PCA and Mutual Information for feature selection.
PREFER: The PREFER framework automates the evaluation of different combinations of molecular representations and machine learning models for predicting molecular properties, utilizing AutoSklearn for model selection and hyperparameter tuning.
ROBERT:
SPOC: An integrated Python package for molecular descriptor generation, data processing, model training, and hyper-parameter optimization, aimed at facilitating the development of predictive models in the field of cheminformatics. .)
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