HOUSE PRICE PREDICTION
The House Price Prediction project aims to develop a regression model to predict house prices based on various features such as location, size, and other relevant characteristics. Using a dataset (e.g., Boston Housing or Kaggle House Prices dataset), we applied data preprocessing, built a Linear Regression model, and evaluated its performance using metrics like Mean Squared Error (MSE) and R squared. Visualisations, including a correlation heatmap and residual plots, provided insights into feature relationships and model accuracy. The project highlights potential improvements, such as testing more advanced algorithms and refining data preprocessing, to achieve better prediction accuracy.
IRIS FLOWER CLASSIFICATION ANALYSIS
The Iris Classification project aims to classify iris flowers into three species—Setosa, Versicolor, and
Virginica—based on their physical characteristics (sepal and petal length and width). The project utilizes machine learning techniques, specifically the K-Nearest Neighbors (KNN) algorithm, to predict the species of iris flowers based on given measurements.
AnalystGPT — AI-Powered Data Analysis Platform
Production-ready AI SaaS platform using Next.js and FastAPI for real-time analysis of user-uploaded datasets. Includes voice-to-query input with Web Speech API, OpenAI-compatible endpoint integration, authentication with NextAuth and JWT, dynamic chart generation, PDF export, pinned dashboards, ML predictions, and dataset cleaning and comparison.
Fake News Detector
End-to-end NLP pipeline using NLTK preprocessing, TF-IDF vectorization, and Logistic Regression classification, integrated with a real-time News API and deployed as a Streamlit application.
Judgment Bias Detector
NLP-based tool for detecting bias patterns in court judgments using text preprocessing and classification, with a Streamlit dashboard and bias visualizations.
Court Data Fetcher & Mini Dashboard
Automated web scraper and Flask dashboard for real-time court case data with CSV/SQLite storage, PDF export, external API integration, and automated data pipelines.