Real-time Stock-market prediction with machine learning #MLmonday #MachineLearning #StockMarket @victor_basu_360
In a GitHub repository, Victor Basu has developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. He used TensorFlow.js for constructing a machine learning (ML) model architecture, and Kafka for real-time data streaming and pipelining.
Pipelining logs from source to topics.
Topics are subscribed by consumer for real-time ml prediction and model training in parallel.
Construction of tensorflow model in node.js.
Training model with time-series stock market data.
Use tfjs model for real-time prediction.
Update data-base with incoming stock market logs.
Use stored logs for analysis, and model training.
Store performance of the ml model for monitoring purpose.
The entire server architecture is developed with node.js
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