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In this video, we build a complete gold price prediction model using Python and machine learning inside a Jupyter Notebook 📊 You will see how historical gold price data is processed, trained, and evaluated using the Random Forest Regression algorithm. This project is beginner-friendly and perfect for students, data science learners, and anyone interested in financial forecasting 💰 The notebook covers the full workflow from loading the dataset to making predictions and evaluating model performance. ⚙️ How it Works 🔹 Load historical gold price data into Jupyter Notebook 🔹 Perform basic data cleaning and preprocessing 🔹 Select important features for prediction 🔹 Split data into training and testing sets 🔹 Train a Random Forest Regressor model 🔹 Predict gold prices on test data 🔹 Evaluate the model using error metrics 🔹 Visualize actual vs predicted gold prices This approach helps reduce overfitting and improves prediction accuracy compared to simple regression models 📈 🛠️ Settings Used 🧠 Algorithm: Random Forest Regressor 📁 Environment: Jupyter Notebook 🐍 Language: Python 📦 Libraries Used: pandas numpy matplotlib seaborn scikit-learn ⚙️ Model Parameters (as used in the notebook): Number of trees (n_estimators) Random state for reproducibility Train-test split for evaluation 🎯 Who This Video Is For 👨🎓 Students learning machine learning 📊 Data science beginners 💹 Finance and stock market learners 🐍 Python developers practicing ML projects ⚠️ Disclaimer This project is for educational purposes only. Gold price prediction using machine learning does not guarantee real-world trading profits. 👍 If you found this helpful, like the video, share it, and subscribe for more Jupyter Notebook and machine learning projects 🚀 #python #machinelearning #randomforest #mlprojects #gold Social Media links LinkedIn : / shivammandrai TradingView: https://in.tradingview.com/u/Shivam_M... Whatsapp Bussinesss( for personal project ): https://wa.me/919136968664 Git Hub: https://github.com/Shivammandrai Telegram Channel Link (Codes Pine Script) : https://t.me/StrategyCoders Telegram Channel 2 Link (Codes Python): https://t.me/+R-QNl0R5z1E1Nzdl Disclaimer : This Video is not financial advice, it's for educational purposes only highlighting the power of python for finance, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.