Drug Discovery with Python and Machine Learning

Key Features:

Scripts for collecting and preprocessing bioactivity data from the ChEMBL database.
Tools for exploratory data analysis and calculating chemical descriptors.
Python code for building and comparing machine learning models for predictive analytics.
A framework for deploying QSAR models as web applications.

Apply Python and machine learning techniques to real-world bioinformatics challenges.
Contribute to drug discovery efforts using computational drug discovery.

Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
data		data
.gitattributes		.gitattributes
Part_1_collect_bioactivity_data_ML.ipynb		Part_1_collect_bioactivity_data_ML.ipynb
Part_2_Exploratory_Data_Analysis_ML.ipynb		Part_2_Exploratory_Data_Analysis_ML.ipynb
Part_3_Compounds_Descriptor_Dataset_Prep_ML.ipynb		Part_3_Compounds_Descriptor_Dataset_Prep_ML.ipynb
Part_4_Regression_Random_Forest_ML.ipynb		Part_4_Regression_Random_Forest_ML.ipynb
Part_5_Compare_Regressors_ML.ipynb		Part_5_Compare_Regressors_ML.ipynb
README.md		README.md