Forex Market Prediction using Deep Learning Overview This project is an experiment to apply deep learning techniques to predict future market prices in the Forex market. The goal is to leverage advanced time series forecasting models to enhance predictive accuracy and inform trading strategies. Installation and Setup To run this project, follow the steps below: 1. Install Python and Create a Virtual Environment Ensure you have Python 3.8 or later installed. You can check your version by running: Create a Virtual Environment 1. Navigate to the project folder: 2. Create a virtual environment: 3. Activate the virtual environment: - Windows: - Mac/Linux: 2. Install Dependencies Once inside the virtual environment, install the required packages: 3. Download Data The dataset for this project includes historical forex market prices and can be obtained from relevant data sources. For benchmark datasets, you can refer to: - Autoformer Repository - Informer Repository Ensure your dataset is placed inside the data/ folder before proceeding. Changing the Dataset To change the dataset and include

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Data-completeness & trust index (not a profitability rating)