Author: Matthew Rowlandson @Treeless
Cryptosense: Machine Learning based predictions of hourly bitcoin prices based on price history, currency volume and community sentiment. We wanted to see if we could accurately predict future prices in such a volatile market using an LSTM model.
This REPO is the front end for the project.
- NodeJS 8.4+
- MongoDB 3.6 (install this as a service)
First ensure, you have the backend python prediction system and have done all the data collecting. See SMSA.
To run the frontend:
npm install
gulp
- Now, navigate to
http://localhost
in your browser.
- SMSA - Start making daily predictions, only next day prediction
- Cryptosense - Show volume for both hourly and daily prices as a chart
- Final presentation
Final Presentation (April 18th 2016) - 2018-04-06 What the presentation entails:
- Who we are (Photos)? This will be very good. The best part of the presentation.
- What our project is, why we decided to do it
- DEMO of app (quick sneakpeak, highlight how ez pz it is to use)
- Non-technical explanation with Workflow model, how things work. Data gathering, processing, prediction, ui
- Architectural Diagram (UML component model) - UI, apis, interfaces) with (APIs we are using + where we are using them)
- Class Diagrams for each part of the workflow
- How the prediction model works [LSTM, inputs (pattern recognition)] - SUPER TECHNICAL
- Where we started (twitter script for sentiment) : Research we did
- Where we ended up - Making predictions for future price changes (based on sentiment/price)
- Show picture of all out slides merged together, just so people can think for a second.
- Future work (talk about your reading course, exploring other machine learning algos, improving the algorithm to get even more accurate predictions)
- QUESTIONS? :)
After presentation 2 (beta) - 2018-03-02
- prediction model
- Omar wants to see the predicted price for the next day
- Multiple coins - ETH, Ripple, BTC
- Webapp:
- He wants to be able to input an influencer and get their sentiment compared to the bitcoin price
- I want to show influencer tweets on the bitcoin price frame we are showing
- Documentation
-
UMLs for the both the prediction model, AND twitter bot
-
Final Presentation
-- Rest of the weeklies were just chit chat... We ended up choosing to strictly use twitter and sentiment combined with the bitcoin price.
Talking with OMAR - 2017-11-03
- Issue: No subreddit traffic api, has been deprecated
- Recommended Solution: Create a library for subreddit post engagement evaluation. (we can also mine news articles during this process)
- RESEARCH: Papers -> Engagement - HISTORY
- How do they mine? Posts for engagement. Formula? Weights ;)
- Information Retrieval Papers
- Japan, wikipedia, scraping. Rank based on importance. What can we pull from these examples?
- OUTCOME: We need to create a library that will pull in reddit posts from a specific subreddit and rank each post based on upvotes, comments, golded comments, and all out engagement. Then using the ranking system, graph the weights alongside the price of the coin.