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.

Technologies used:

  1. Kafka.kafka
    • Pipelining logs from source to topics.
    • Topics are subscribed by consumer for real-time ml prediction and model training in parallel.
  2. TensorFlow.js.tf
    • Construction of tensorflow model in node.js.
    • Training model with time-series stock market data.
    • Use tfjs model for real-time prediction.
  3. MongoDB.mongodb
    • 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.
  4. Node.jsnode
    • The entire server architecture is developed with node.js

Read more in GitHub here.

 


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