Gold Price Prediction Project

Welcome to the Gold Price Prediction Project! This repository contains a Python-based application designed to forecast gold prices using advanced quantitative analysis, machine learning, and deep learning techniques.

Features

• Data Collection: Historical gold price data and relevant economic indicators.
• Machine Learning Models: Implementation of various algorithms, including Linear Regression, Random Forest, and XGBoost.
• Deep Learning Models: Utilization of LSTM and CNN architectures for enhanced prediction accuracy.
• Performance Evaluation: Comprehensive metrics to assess model performance.
• Visualization Tools: Graphical representations of predictions versus actual prices.

Table of Action Names and Scores

The following table summarizes the performance scores of various trading actions implemented in this project:

Action Name	Score
NaviBase	51%
MACD	61%

Technologies Used

• Python
• Pandas, NumPy, Scikit-learn, TensorFlow/Keras, Matplotlib, Seaborn

Getting Started

To get started with this project:

1. Clone the repository.
2. Install the required libraries using pip install -r requirements.txt.
3. Follow the instructions in the python terminal folder for data processing and model training.

Contributing

We welcome contributions! Please feel free to submit issues or pull requests to help improve this project.