Notebooks about Bayesian methods for machine learning
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Updated
Mar 6, 2024 - Jupyter Notebook
Notebooks about Bayesian methods for machine learning
A collection of Bayesian data analysis recipes using PyMC3
Machine learning resources (Jupyter notebooks mostly). Originally code to complement the "EECE 5644: Introduction to Machine Learning and Pattern Recognition" course taught at Northeastern University.
Notebooks for Bayesian Foundations (Course 1)
🫧 Learning the different implementation approaches of bayesian methods using Python (Jupyter Notebook).
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 project contains a collection of Jupyter Notebook files related to optimization algorithms including Hill Climbing, Genetic Algorithm, Iterated Local Search, Simulated Annealing, and Tabu Search.
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