Understand and Run Naive Bayes Algorithm on Dry Beans dataset

Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21

Navie Base Classifier for classifiing imdb comments

ML methods used for vehicle ECU Classification along with simulating the intrusion.

This is the repository for the EDAN95 - Tillämpad maskininlärning (Applied Machine Learning) course given at Lunds Tekniska Högskola (LTH) during the Fall 2019 term.

Supervised Machine Learning models and Neural Networks trained on a bevy of feature extractors for Sarcasm Detection with a better Pre-processing approach

This is a project that was done for the Skill4U machine Learning program. This project is a Spam email classifier using machine learning. This model uses Gaussian NB algorithm to train the model.

A model to extract comments from a YouTube video to create a dataset and to apply sentiment analysis that provides the YouTuber with a better understanding of viewer sentiment distribution.

This repository contains the code for a machine learning project - Diabetes Prediction. In this project, a model is built to find the relationship between the features and the associated outcome and classify the patient as Diabetic or Non-Diabetic. The Gaussian Naive Bayes Classifier Model is used for this purpose.

Classifying species for Iris samples using different ML algorithms (Logistic Regression, K-Nearest Neighbor, Support Vector Machines with different kernels, Gaussian Naive Bayes)

Prediction of creditworthiness for issuing a credit card

A prediction model based on ML as well as DL and compare their performances to find Churned Customers

Bayesian inference implementation and comparing accuracy against Sklearn

Implementation of different types of machine learning algorithm and there performance comparison on a same dataset