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stockprice-prediction

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This project employs LSTM, a type of recurrent neural network, to forecast stock market indices using historical data with features like date, open, high, low, close, and volume. By training the model on this dataset, it learns patterns to predict future market trends, aiding investors, traders, and analysts in decision-making.

  • Updated Feb 8, 2024
  • Jupyter Notebook

A comprehensive suite of Python-based machine learning models for predictive analytics, employing different evolutionary algorithms for data analysis across various topics.

  • Updated Apr 11, 2024
  • Python

In this project, I applied sentiment analysis using a statistical machine learning model to capture the correlation between the tweets extracted from Twitter and stockโ€™s price market movements. My exploration sought to answer if daily stock prices behave in response to a positive, neutral, or negative sentiment scoring of respective tweets

  • Updated May 26, 2024
  • R

๐Ÿ“ˆ๐Ÿ’ฐ Predict stock prices with a linear regression model and 50DMA data ๐Ÿš€ ๐ŸŽฏ Make informed investment decisions ๐Ÿง ๐Ÿ’ฐ ๐Ÿ‘ฉโ€๐Ÿซ๐Ÿ‘จโ€๐Ÿซ Train a model and generate predictions ๐Ÿ”ฎ ๐Ÿค Contribute to the future of stock prediction ๐Ÿš€

  • Updated Nov 24, 2023
  • Jupyter Notebook

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