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.

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

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

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

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

Interactive Tool for Interpreting positive COVID-19 antibody tests

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

Implementation of Naive Bayes & Bayes Theorem

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