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Trend Pulse

Trend Pulse

Navigating Tomorrow's Markets with LSTM Intelligence 🏆 The Winners At ThinkML by AltAir

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Created on 22nd February 2024

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Trend Pulse

Trend Pulse

Navigating Tomorrow's Markets with LSTM Intelligence 🏆 The Winners At ThinkML by AltAir

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The problem Trend Pulse solves

Trend Pulse is an ML-powered stock price prediction app built with Python and Streamlit. It utilizes machine learning models to forecast stock prices and help investors make data-driven decisions.

Challenges I ran into

  1. Cleaning the Dataset and reducing the Noise.
  2. Cutting Down Training Time to 40 Seconds.
  3. Enhancing Model Accuracy More Data, the Greater the Precision.
  4. Better Optimization of the Model.
  5. Legal and Ethical Considerations.

Technologies used

Streamlit - To create the web app UI and interactivity

LSTM - To build the Long Short Term Memory model

Plotly - To create interactive financial charts

Keras - To Train the model layer by layer.

Tensorflow - To link the layers with the model.

Discussion

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