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In this project we will explore about Bitcoin and also we will predict the price of bitcoin using Machine Learning algorithm..Here we will use LSTM model in Tensorflow to build our model and then we will predict the bitcoin price.
Epoca Compose is a CLI designed to perform sensitive operations and can run without an active Internet connection, takes care of managing the project's containers by making use of Docker Compose and interacts directly with the server through SSH.
Epoca Core API is a RESTful API that can be interacted with through the GUI. It is designed to manage the platform as well as the implementation of the Value Averaging Strategy.
LSTM (Long Short-Term Network) is a kind of Recurrent Neural Network which used in the field of deep learning. Traditional neural networks can't remember previous inputs. But Recurrent Neural Networks enable us to learn from previous sequence input datas. A LSTM unit is composed of a cell, an input gate, an output gate and a forget gate.
The Epoch Builder is a cluster of machines designed to train and evaluate many Prediction Models. It also outputs an Epoch File that can be installed in Epoca's Platform.
Developed a binary classification algorithm for Bitcoin price prediction at different frequencies ( daily price and 5-minutes interval price) using different machine techniques model in Python
This thesis aims to test an innovative and untested approach to classify the price of Bitcoin in a way that can later be used on algorithmic trading scenarios by using a 2D Convolutional Neural Network.
In this project, analysis and prediction of the bitcoin price was carried out as part of a project to research artificial intelligence in finance in the scope of Interactive ML course at Augsburg University