An attempt to build predictive models using machine learning and deep learning algorithms including Linear Regression and LSTM to predict the prices of bitcoin and used matplot and seaborn libraries to visualize the evaluation metrics.

With each passing year, Cryptocurrencies have been gaining immense popularity and are being adopted by many governments all over the world. Cryptocurrencies are digital currencies, also referred to as coins, that use cryptography to secure transaction records that are created on trading coins over the internet. Through this project, we aim to build a machine learning model that would mitigate risk factors associated with Cryptocurrency price prediction. This project shall address the problem of predicting cryptocurrency rates using machine learning algorithms. Three machine learning algorithms have been used in this project, namely, Support Vector Regression (SVR), Linear Regression and Long short-term memory (LSTM). After model evaluation, it could be seen that, long short-term memory (LSTM) has a better accuracy as compared to the other Machine Learning models. Total files include in this project:

1. README.md
2. project_svm_rbf-finalDraft.ipynb
3. project_svm_linearkernel-finalDraft.ipynb
4. project_linear_regression_finalDraft.ipynb
5. LSTM_project_finalDraft.ipynb

https://www.youtube.com/watch?v=0JckqfIgI6k