Stock Prediction using Neural Networks
We build models that learn non-linear patterns from market history and deliver fast, repeatable predictions in a browser. These models are practical, data-driven, and grounded in observed past performance.
The interface is simple. Select a ticker, review the latest available data, and generate the next-day closing prediction. This makes it easy to compare the model’s output against real market movement and build intuition around when machine learning can help.
Stock prediction is a challenging problem. Machine learning offers a structured way to learn from data and test ideas quickly.