All My Projects

Class 9 PDF-based Chatbot
PDF-based Chatbot

PDF Chatbot: Query Textbooks for Subject Answers in English & Hindi

View on GitHub
AI-Driven Portfolio Management
Portfolio Management

Uses LSTM and Transformer models to predict asset returns and apply them in dynamic asset allocation and portfolio evaluation.

View on GitHub
Gesture-Controlled Device Management
Gesture-Controlled Device Management

Use hand movements to manage device settings like volume and brightness.

View on GitHub
Blindness Detection
Blindness Detection

Automated Diabetic Retinopathy detection using ResNet50, 96.17% training accuracy.

View on GitHub
Movie Recommendation System
Movie Recommendation System

Uses a content-based filtering approach to recommend movies similar to a user's favorite movie using NLP and cosine similarity.

View on GitHub
Fake News Detection
Fake News Detection

Uses machine learning and Logistic Regression to detect fake news articles by predicting the label of new unseen news.

View on GitHub
Medical Insurance Prediction
Medical Insurance Prediction Using Linear Regression

Predicts medical insurance costs based on features such as age, sex, BMI, children, smoker status, and region using Linear Regression.

View on GitHub
House Price Prediction with XGBoost
House Price Prediction with XGBoost

Uses the XGBoost regression model to predict house prices based on the California Housing dataset. It includes data preprocessing, EDA, model training, and evaluation.

View on GitHub
Customer Segmentation using K-Means
Customer Segmentation using K-Means Clustering

Uses the K-Means clustering algorithm to segment customers based on the Mall_Customers dataset. It includes data preprocessing, clustering, and visualization using plots.

View on GitHub
Breast Cancer Detection ML Model
Breast Cancer Detection ML Model

Uses Logistic Regression to predict the presence of breast cancer based on a dataset, classifying tumors as malignant or benign. The model has a training accuracy of 98% and a test accuracy of 96%.

View on GitHub
Calories Burnt Prediction using XGBoost
Calories Burnt Prediction using XGBoost

Uses the XGBoost gradient boosting algorithm to predict the number of calories burnt based on various exercise and demographic datasets. The model evaluates feature importance and performance.

View on GitHub
Back to Portfolio