Notebooks about Bayesian methods for machine learning

Python Scripts and Jupyter Notebooks

Finding the best parameters for any algorithm

A jupyter notebook for binary classification of breast cancer using XGBoost with Bayesian optimization.

✨My kaggle notebooks

Notebooks and code snippets demonstrating machine learning techniques.

This notebook demonstrates timeseries classification for crop identification on a subset of the MiniTimeMatch dataset by training an LSTM model.

Implementation, analysis and benchmarking of optimization algorithms. Developed in Python and results showed in Jupyter Notebook

Concepts of Bayesian Statistics, Bayesian inference, computational techniques and knowledge about the different types of models as well as model selection procedures.

A collection of presentations and notebooks on machine learning for automated experiments

This Jupyter Notebook implements Bayesian modeling techniques to fit a posterior distribution and forecast demand for an e-commerce company.

Bayesian Optimization for hyperparameter tuning in machine learning using a Jupyter Notebook. This repository demonstrates optimizing a Gradient Boosting Classifier with practical examples and clear explanations.

This repository provides tools for forecasting Great Britain’s power demand using Facebook’s Prophet model. It includes Python functions and Jupyter notebooks for daily and monthly forecasts, integrating weather and GDP as regressors, with hyperparameter tuning via HyperOpt.