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This repository contains the implementation of Gaussian Naive Bayes from scratch in a Jupyter Notebook. Gaussian Naive Bayes is a simple and effective algorithm for classification tasks. It is based on Bayes' theorem with the assumption of independence between the features.
The Coffee Bean Sales Dataset offers a multifaceted exploration of the thriving coffee industry, providing a comprehensive view of sales, customer profiles, and coffee product details. This rich dataset is a gateway to understanding consumer behavior, optimizing product offerings, and improving business strategies in the world of coffee.
In this mini-project, I engage in solving practice problems related to probabilities before transitioning to explore various statistical distributions.
Project involved the analysis of a covid-19 dataset, applying bayes theorem to estimate probabilities and using KNN ML algorithm to train a model and make predictions based on the data