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Added sri_pipelines.md with API resources and control flow (#5)
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TODO_PIPELINES/sri_pipelines.md

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Sports:
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* https://www.mysportsfeeds.com/
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* https://www.thesportsdb.com/
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* https://developer.sportradar.com/getting-started/docs/get-started
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Finance:
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* https://www.alphavantage.co/
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* https://finnhubio.github.io/
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* https://developer.yahoo.com/api/
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Control flow:
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1. Data Retrieval
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- Python scripts to fetch sports and market data from the API
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- Store the API responses in a database (MongoDB)
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2. Data Extraction/Processing
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- Extract relevant features such as player information, team statistics, market data, etc (using Numpy and Pandas)
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- Store the tables using AWS if needed
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3. Model Training
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- Model training logic, weights assignment and updating, etc.
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- Scikit-learn and TensorFlow
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4. Model Deployment
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- Flask or FastAPI for real-time predictions given a user request
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5. Frontend
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- React.js and Next.js to allow users to pick between sports and finance markets, input queries, view predictions, and visualize trends
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- No need for user accounts and login/logout authentication (yet)
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Potential additions:
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After an event predicted by the model occurs, retrain the model based on the result of the event.

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