Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

Overview

Price-Prediction-Model

This project’s goal is to develop a machine learning model that can predict a cryptocurrency's future market price.

A LSTM model is trained on historical price data that is pulled in through an API and stored in a relational database.

The model attempts to predict prices for a chosen time window, for both Bitcoin and Ethereum.

Our app is deployed using Heroku:

https://price-prediction-model.herokuapp.com/

Dataset:

The daily crypto price data has been pulled in through an API on CryptoCompare:

https://min-api.cryptocompare.com/documentation?key=Historical&cat=dataHistoday

The pricing information includes: timestamp, high, low, open, volumefrom, volumeto, and close. We will most likely save all the data, but only use one of the pricing metrics to train the model.

ETL proccess

The API data includes timestamp, high, low, open, volumefrom, volumeto, and close. In addition to these columns, we've created a coin, date, and year column.

Data storage

  • We used Heroku Postgres to store data for our app.
  • The database updates only when needed, based on the current and last unix timestamp in the db Database updates up to once daily, when index page loads, based on 00:00 GMT time zone.
  • Time units were daily only.
  • Data for both coins was stored in 1 table, due to limitations of a free Heroku Postgres database.

Long Short Term Memory (LSTM) Model

The Long Short Term Model (LSTM) has been used to do the price forecasting. LSTM is a slightly more sophisticated version of a Recurrent Neural Network (RNN) which incorporates long term memory. The model will be trained on historical price data and used to predict the next value in the series. (Time window for predictions, tbd)

Visualization

HTML/CSS/Plotly has been used to do the visualization and plots. Here are the final plots and Welcome page:

Welcome Page:

Bitcoin PricePerformance Plot and Table:


Bitcoin Candlestick chart:

Bitcoin Price Prediction Model:

Bitcoin Price Acceleration Plot:

Ethereum Price Performance Plot and Table:

Ethereum Candlestick Plot:

Bitcoin vs Ethereum Comparison Table and Plot:


Team Members:

Anna Weeks
Hima Vissa
Jacob Trevithick
Lekshmi Prabha
Diabetes Prediction with Logistic Regression

Diabetes Prediction with Logistic Regression Exploratory Data Analysis Data Preprocessing Model & Prediction Model Evaluation Model Validation: Holdou

AZİZE SULTAN PALALI 2 Oct 23, 2021
Datetimes for Humans™

Maya: Datetimes for Humans™ Datetimes are very frustrating to work with in Python, especially when dealing with different locales on different systems

Timo Furrer 3.4k Dec 28, 2022
Neural Machine Translation (NMT) tutorial with OpenNMT-py

Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.

Yasmin Moslem 29 Jan 09, 2023
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.

Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led

Brett Vogelsang 2 Jan 18, 2022
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.

Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi

BentoML 4.4k Jan 04, 2023
Applied Machine Learning for Graduate Program in Computer Science (PPGCC)

Applied Machine Learning for Graduate Program in Computer Science (PPGCC) - Federal University of Santa Catarina

Jônatas Negri Grandini 1 Dec 22, 2021
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

Jesùs Guillen 1 Jun 03, 2022
ML-powered Loan-Marketer Customer Filtering Engine

In Loan-Marketing business employees are required to call the user's to buy loans of several fields and in several magnitudes. If employees are calling everybody in the network it is also very length

Sagnik Roy 13 Jul 02, 2022
Factorization machines in python

Factorization Machines in Python This is a python implementation of Factorization Machines [1]. This uses stochastic gradient descent with adaptive re

Corey Lynch 892 Jan 03, 2023
TensorFlow implementation of an arbitrary order Factorization Machine

This is a TensorFlow implementation of an arbitrary order (=2) Factorization Machine based on paper Factorization Machines with libFM. It supports: d

Mikhail Trofimov 785 Dec 21, 2022
machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service

This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made th

Krishna Priyatham Potluri 73 Dec 01, 2022
Tools for Optuna, MLflow and the integration of both.

HPOflow - Sphinx DOC Tools for Optuna, MLflow and the integration of both. Detailed documentation with examples can be found here: Sphinx DOC Table of

Telekom Open Source Software 17 Nov 20, 2022
Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning

Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My

3 Apr 10, 2022
Ml based project which uses regression technique to predict the price.

Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with

Garvit Verma 1 Jul 09, 2022
A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement.

Organic Alkalinity Sausage Machine A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement. Getting started To mak

Charles Turner 1 Feb 01, 2022
Lightning ⚡️ fast forecasting with statistical and econometric models.

Nixtla Statistical ⚡️ Forecast Lightning fast forecasting with statistical and econometric models StatsForecast offers a collection of widely used uni

Nixtla 2.1k Dec 29, 2022
EbookMLCB - ebook Machine Learning cơ bản

Mã nguồn cuốn ebook "Machine Learning cơ bản", Vũ Hữu Tiệp. ebook Machine Learning cơ bản pdf-black_white, pdf-color. Mọi hình thức sao chép, in ấn đề

943 Jan 02, 2023
💀mummify: a version control tool for machine learning

mummify is a version control tool for machine learning. It's simple, fast, and designed for model prototyping.

Max Humber 43 Jul 09, 2022
High performance Python GLMs with all the features!

High performance Python GLMs with all the features!

QuantCo 200 Dec 14, 2022
SynapseML - an open source library to simplify the creation of scalable machine learning pipelines

Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy

Microsoft 3.9k Dec 30, 2022