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APPLE Stock Market Prediction Using LSTM and deep stacked multi LSTM layers

License: GNU General Public License v3.0

Jupyter Notebook 100.00%
apple deep-learning investment lstm market-analysis market-data prediction prediction-model stock

apple-stock-market-prediction-using-lstm's Introduction

Apple Stock Market Prediction Using Python and Deep Neural Networks LSTM

I gathered stock market data from Apple from the very beginning and predicted the possible results for the next week with deep learning techniques. RMSE values turned out to be quite small which is unusual given how volatile stock markets are. Apple's stock data was obtained as data until 2021 and developed using the Python programming language a multi- layered deep learning model with LSTM structure based on old data. The algorithm has successfully predicted the stock market closing prices of the coming days with very small margins of error.

💻 Built with

Technologies used in the project:

  • Python
  • LSTM (Long Short Term Memory)
  • TensorFlow
  • Keras
  • Pandas
  • Numpy
  • Deep Learning
  • Kaggle
  • Prediction
  • Anaconda
  • Jupyter Notebook

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