- Introduction
- Test on HuggingFace
- Repository Contents
- Custom Order
- Contact Information
- Related GitHub Repositories
- Other Products
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Backtest telegram messages from a whole channel about trading (stocks or crypto) using Machine Learning (Named Entity Recognition or Token Classification).
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Data Conversion Script
Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset:
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Train NER Model
Train the NER model using HuggingFace-autoTrain:
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Predict Labels
Use the model to predict labels on new data in LabelStudio:
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Python Prediction Function
Define a Python function to predict labels using the model:
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Label New Data
Only label new data from newly predicted-labels-dataset that has falsified labels:
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Backtest Data
Backtest truly labeled dataset against real historical data of the stock:
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Evaluate Performance
Evaluate total gained percentage since inception summation-wise and compounded, then plot:
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Live Telegram Channel Listening
Listen to the telegram channel for new live messages using the Telegram API for algo trading:
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Flask API
Serve the app as a Flask web API for web request and respond to it as labeled tokens:
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Performance Against Exchange Index
Outperforming or underperforming results of the telegram channel tips against the exchange index by percentage:
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Ready to elevate your trading strategy?