Optimization for Machine Learning mini-project: Random search comparisons for hyperparameter optimization
Research mini-project for the CS-439 Optimization for Machine Learning Course.
Designed, Benchmarked and assessed random search algorithms for hyperparameters optimization.
We decided to focus our research in hyperparameter optimization. We benchmarked different models - classical ones like manual fine-tuning and grid search, but also more uncommon ones like random search. We also benchmarked our own extended random search in this mini-project.
We decided to use a public [Heart Attack Dataset]{https://www.kaggle.com/rashikrahmanpritom/heart-attack-analysis-prediction-dataset}
You can find our report which summarize our work, research and result in the report.pdf file
You can find our code in the Opti_for_ML.ipynb file