MLLib: Predicting Stock Movements from the News

Published by pschatzmann on

In this blog we will demonstrate how we can predict if a stock is going up or down based on the news headlines. The solution consists of the following components:

  • Spark MLLib (Machine Learning)
  • My News-Digest (which I have described in my last blogs)
  • Investor (we determine the stock prices to calculate the labels )

 

see also:

  1. Deeplearning4j – Recurrent Neural Networks (RNN)
  2. Deeplearning4j – Iris Classification Example
  3. Random Forrest Classifier in Spark ML
  4. H2O Sparkling Water – Distributed Random Forrest
  5. Using Shogun in the JVM
  6. Docker + WordPress = Danger
  7. PWM Support for my Raspberry Pico Arduino Framework
  8. Machine Learning on the Rasperry Pico
  9. Serving WordPress from a Mobile Network
  10. Naive Bayes with Weka
Categories: Data ScienceMachine LearningNews Digest

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