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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.
In this mini-project, I engage in solving practice problems related to probabilities before transitioning to explore various statistical distributions.
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.
This repository has been created to complete an assignment given by datainsightonline.com. This assignment is a part of Data Insight | Data Science Program 2021.
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