Automated Machine Learning (AutoML) for Drug Discovery
About Course
- Tech Stack: Python (Auto-sklearn, H2O.ai), Jupyter, Docker, Kubernetes, GCP (AI Hub, BigQuery)
- Objective: Develop an AutoML pipeline that can automatically select and tune machine learning models for drug discovery datasets. The system will search through hyperparameters, automate feature engineering, and handle large-scale bioinformatics data.
- Skills Needed: AutoML, cloud integration (GCP), bioinformatics datasets, hyperparameter tuning, model deployment via Kubernetes.
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