Cryptocurrency Price Predictor

This repository contains a Jupyter Notebook (crypto_price_prediction.ipynb) demonstrating the prediction of cryptocurrency prices using a Long Short-Term Memory (LSTM) neural network.

Overview:

• Data Collection: The notebook fetches historical cryptocurrency price data from the CryptoCompare API.
• Data Preprocessing: It preprocesses the data by scaling and sequencing it for input into the neural network.
• Model Building: An LSTM neural network is built, trained, and evaluated to capture temporal dependencies in the time series data.
• Prediction: The trained model is used to iteratively predict cryptocurrency prices for the next several days.
• Visualization: Historical prices are plotted along with the predicted prices for better visualization and analysis.

How to Use:

1. Clone the Repository:

   git clone https://github.com/nirnaim/crypto-price-predictor.git

2. Open the Jupyter Notebook:
   • Navigate to the repository directory.
   • Open crypto_price_prediction.ipynb in Jupyter Notebook or Jupyter Lab.
3. Follow the Steps:
   • Execute each cell in the notebook to collect data, preprocess it, train the model, and make predictions.

Dependencies:

• pandas
• numpy
• matplotlib
• scikit-learn
• tensorflow or keras

Contributions:

Contributions are welcome! Feel free to open an issue or submit a pull request for any improvements or bug fixes.

License:

This project is licensed under the MIT License.