Diabetes Prediction is my weekend practice project. In this I used KNN Neighbors Classifier to trained model that is used to predict the positive or negative result. Given set of inputs are BMI(Body Mass Index),BP(Blood Pressure),Glucose Level,Insulin Level based on this features it predict whether you have diabetes or not.

It is a best Visualiser for implementing K-Nearest Neighbours Algorithm with 3 different classes i.e A,B,C. It is developed using ml5.js and p5.js.

This repo contains of various components of the Interactive web app : Edu Squad , designed on the theme of Adaptive Learning. Features are implemented, so as to help make the virtual Learning fun & efficient

A machine learning Flask application for predicting cancer is Malignant or Benign

predict the winning horse with supervised machine learning models (lucky to have 100% accuracy on small test data)

Classification model for 1 year survival rates in patients with HCC (hepatocellular carcinoma).

Classification problem

Klasifikasi buah alpukat berdasarkan warna menggunakan algoritma KNN

The projects displayed are part of my course in Great Learning - Business Analytics and Business Intelligence

Analysis to predict the trust value of a borrower, such a way the bank sanctions the loan or not

I would like to use ML to help high school students focus on the factors that really affect the college admission process and help them to get admitted.

Predicting whether or not a cell has cancer.

ML Precipitation Prediction

Crop Recommendation Using Machine Learning(KNeighborsClassifier) and OpenWeatherMap

A case-based reasoning application to predict the sentence of a new lawsuit

The goal of this project is to create a classifier and see how accurately it can predict song genres. Taking a dataset from Spotify [Pandya, 2022], which is al- ready using machine learning algorithms for these purposes, can help assess if the resulting model can be considered apt for a large-scale business.

COMPREHENSIVE WEB-BASED RECOGNITION SYSTEM FOR MULTI MODEL ANALYSIS

A Team Project on developing COVID-19 predictor with chest X-Ray images as dataset under Data Science with R subject of Otto-von-Guericke-University, Magdeburg

A functional real time ML based system for predicting constituents (dosha) in human body.

A comprehensive project with scraping data, methodology, including graph construction, common subgraph identification, KNN implementation, and classification results.