Instructions to use jsebdev/apple_stock_predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use jsebdev/apple_stock_predictor with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://jsebdev/apple_stock_predictor") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model description
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## Intended uses & limitations
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## Model description
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This model predicts Apple stock prices. The model takes as input the last 500 daily candles of Apple stocks data and outputs the predicted candle for the next day. The input candles must be in chronological order, representing daily data for each candle, and the predicted candle will also be in daily format.
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## Intended uses & limitations
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