A category-guessing model, trained with bayes theorem
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Updated
Oct 24, 2023 - Jupyter Notebook
A category-guessing model, trained with bayes theorem
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.
Estimate conditional probabilities, compare data distributions, and perform data transformations to analyze employee absences
School activities on application of Bayesian Statistics in Python.
Implementation of Bayes and naive Bayes for iris dataset
Implementation of Naive Bayes & Bayes Theorem
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.
Vrinda Store wants to create an annual sales report for 2022. So that, Vrinda can understand their customers and grow more sales in 2023
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
Naive Bayes Classifier that utilizes Bayes theorem and normal distributions.
This project aims to understand and build Naive Bayes classifier to predict the salary of a person.
ML Topics include KNN. Naive Bayes and Support vectors both in Theory and Python Code. KNN Imputation technique is also explained in this branch.
Fast explication of Gaussian NB
A full page Bayes' Theorem interactive visual
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.
Interactive Tool for Interpreting positive COVID-19 antibody tests
A geometric interpretation of Bayes Theorem showing how dependent probabilties relate to each other.
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