• Stars
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    8
  • Rank 2,099,232 (Top 42 %)
  • Language
    Python
  • Created over 5 years ago
  • Updated about 3 years ago

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Repository Details

This projects allows users to predict stock prices through the use of scikit-learn to train a support vector regression on a Google Finance dataset (apple in this case). The code produces a graph showing the 3 model used: RBF, Linear, and Polynomial (RBF turned out to be the best one). The Machine Learning model can be adjusted to Keras, as well, to adapt it to Neural Networks. A further upgrade might be prediction of stock prices by using sentiment analysis and price history.

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