This project focuses on predicting gold prices using historical data and machine learning techniques. It demonstrates a complete data science workflow, including data preprocessing, exploratory data analysis, feature engineering, model training, evaluation, and result visualization using Python.

FastAPI-based gold price prediction system using machine learning. Trained model and API for seamless usability. 📈🤖

A Python project that forecasts gold prices using machine learning and deep learning techniques, leveraging historical data and economic indicators for accurate predictions. If you need further modifications, just let me know!

Developed Random-Forest-based machine learning model to precisely predict gold prices, achieving 85% accuracy in testing conditions. Integrated large datasets to generate forecasts for near-term price fluctuations.

Nostradamus is a powerful and adaptable project designed to predict future outcomes across various domains. Its current focus is on forecasting the gold spot price for a given date, but it is built as a scalable foundation for expanding into a wide range of predictive applications.

It a Gold Price Impact and LTV Risk Analysis dashboard. I built it to understand how companies like Rupeek or Muthoot assess lending risk. The project involves 45 years of gold price data, forecasting future prices, simulating a loan portfolio of 500 customers, and calculating real-time LTV

A machine learning model for predicting gold prices using a Random Forest Regressor, featuring data analysis and a web interface built with Streamlit.

This App is For calculating Gold Price in INR using USD/INR Exchange Rate

Streamlit app for visualizing and forecasting gold prices using ARIMA time series modeling.

Transforming 10+ years of gold price data into precise forecasts using LSTM neural networks for Indonesia’s market trends.

Developed a Streamlit-based web app featuring regression prediction projects for House Price, Car Price, Gold Price, Medical Insurance Cost, Big Mart Sales, and Calories Burnt using various machine learning models.

Gold Price Prediction using Random Forest Regressor

Gold Price Prediction using Random Forest algorithm to accurately forecast future gold prices based on historical data

AI-powered GLD ETF price prediction using KNN Regression | Flask web app with 11 market indicators | R2 ~ 99.8%

Gold Price Prediction and Real-Time Anomaly Detection

This project uses a Random Forest Regressor to predict gold prices based on financial indicators like SPX, Oil, Silver, and USD Index. The model is trained on historical data and deployed as an interactive Streamlit web app for real-time predictions.

Gold Price Prediction

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Predicts gold prices using a Random Forest Regressor, trained on historical market data with feature engineering and performance evaluation.

🏦 Analyze gold price trends and assess Loan-to-Value risks using machine learning to enhance decision-making for financial institutions and lenders.