Predict Diabetes using Machine Learning and deployment of machine learning model using Django.

This repository classifies mushrooms as poisonous or edible using various machine learning algorithms

Classification of obstructive and non-obstructive pulmonary diseases on the basis of spirometry using ML

An online interface for water quality and leakage detection based on pH, temperature, turbidity, hardness and valve pressure. Employs SVM & LR at its core.

DGF AI Analysis, from Exploratory Data Analysis, Handling Missing Data, to Predicting DGF with various Machine Learning Model such as Logistic Regression, Support Vector Machine, Gradient Boosting, and Random Forest

The purpose of this Attendance System Using Face System is to record the presence or attendance of employee through a browser by recognizing the faces captured through a webcam. For this record-keeping, a database was built to store the in-time and out-time of the employee.

Multinomial classification tasks in Reddit

data science and machine learning

Customer Churn Prediction

A Comparative Study in Customer Churn Prediction through Multilayer Perceptrons and Support Vector Machines

A website visualising various classification algorithms

Time Series Prediction on COVID-19 using Support Vector Machine (SVM), Bayesian Ridge, and Polynomial Regression

Study of the Spatial Pyramid kernel function for Support Vector Machines (SVMs) and implementation of its statistical learning paradigm for image recognition. 🧱

This project detects spam messages in SMS, including those written in regional languages typed in English. It uses an extended SMS dataset and applies the Monte Carlo method with various supervised learning algorithms to improve spam detection.

Verify banknote specimens using various classification algorithms on Wavelet-Transformed images

To predict patients with breast cancer using classification models such as random forest, support vector machine, and stacking ensemble method

Machine Learning Prediction Model implemtation in webapp for easy access

Detect hate speech in real-time using an LSTM-based deep learning model with Flask. Includes text preprocessing, live predictions, and a user-friendly web interface.