Interactive Visual Machine Learning Demos.

This project aims to predict the type 2 diabetes, based on the dataset. It uses machine learning model,which is trained to predict the diabetes mellitus before it hits.

Breast Cancer Diagnosis using machine learning algorithms | Deep Learning | Logistic Regression | API | Frontend | Backend |

This project is a development of Flask Application called 'Know It' which consists of three different prediction codes which are Pizza Liking Prediction, Fuel Price Prediction and Diabetes Prediction.

Breast Cancer Classifier using Logistic Regression

AI Text Detection Web App identifies whether text is AI-generated or human-written. It offers unigram and bigram models, combining Logistic Regression, Naive Bayes, Random Forest, and LightGBM to provide accurate predictions based on text structure and context.

Logistic Regression model trained to determine if someone will survive the Titanic disaster, dressed in a Flask API and deployed on Heroku.

This project objective is to predict the type 2 diabetes, based on the dataset.

Twitter Sentiment Analysis is a mini project that utilizes Logistic Regression to classify tweets as either positive or negative. The project includes an API endpoint built with FastAPI, allowing users to submit a tweet's URL and receive a sentiment analysis response.

This is an Web Application to predict the IPL Match winner.

This Project will help us to make better choices the appropriate crop for the soil based on several factors.

Sentiment Analysis of Tweets During Covid Period https://infysoars-project-covid.infysoars.repl.co/dashboard

Attended the LanHack conducted by Lancaster University - Lancaster, UK and developed a ML-based model to classify Malicious and Non-Malicious URLs.

Portfolio projects

A machine learning project aimed at predicting the likelihood of heart disease based on patient data. This repository contains data preprocessing, model training, evaluation scripts, and visualization tools to analyze and interpret results. Ideal for healthcare analytics and research. This Model Have Accuracy rate is 80 percent.

In statistics, the logistic model (or logit model) is used to model the probability of a certain class or event existing such as pass/fail, win/lose, alive/dead or healthy/sick. This can be extended to model several classes of events such as determining whether an image contains a cat, dog, lion, etc. Each object being detected in the image woul…

Login-registration form, design

This is a Django application for predicting whether the sentiment of a financial news headline is positive, negative or neutral (from an investor point of view)