Diffusion Classifier leverages pretrained diffusion models to perform zero-shot classification without additional training

Quizzes & Assignment Solutions for Data Science Math Skills on Coursera. Also included a few resources on side that I found helpful.

about statistical techniques for Data Science

A work to explore discriminative abilities in frozen pretrained generative models.

This project aims to understand and build Naive Bayes classifier to predict the salary of a person.

A Naive Bayes Text Classifier that classifies input text into one of two categories: either a BUSINESS article or a SPORT article

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.

Exercise solution to the Probability Theory course

A geometric interpretation of Bayes Theorem showing how dependent probabilties relate to each other.

Jupyter Notebook featuring hands-on exercises centered around Bayesian networks and Bayesian classifiers.

💬 Conditional Probability Clearly Explained

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

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.

ML Topics include KNN. Naive Bayes and Support vectors both in Theory and Python Code. KNN Imputation technique is also explained in this branch.

Interactive Tool for Interpreting positive COVID-19 antibody tests

A series of R scripts I wrote while following along with the book Statistical Rethinking - @rmcelreath while preparing for the Modern Actuarial Statistics II Exam @casact

A category-guessing model, trained with bayes theorem

School activities on application of Bayesian Statistics in Python.

Implementation of Bayes and naive Bayes for iris dataset

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.