Instructions to use joyjitroy/Bank_Churn_Prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use joyjitroy/Bank_Churn_Prediction with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://joyjitroy/Bank_Churn_Prediction") - Notebooks
- Google Colab
- Kaggle
Rename _Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks.ipynb to Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks.ipynb
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_Bank_Customer_Churn_Prediction_using_ANN.ipynb filter=lfs diff=lfs merge=lfs -text
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Bank_Customer_Churn_Prediction_using_ANN.ipynb filter=lfs diff=lfs merge=lfs -text
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Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks[[:space:]](1).ipynb filter=lfs diff=lfs merge=lfs -text
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_Bank_Customer_Churn_Prediction_using_ANN.ipynb filter=lfs diff=lfs merge=lfs -text
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Bank_Customer_Churn_Prediction_using_ANN.ipynb filter=lfs diff=lfs merge=lfs -text
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Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks[[:space:]](1).ipynb filter=lfs diff=lfs merge=lfs -text
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Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks.ipynb filter=lfs diff=lfs merge=lfs -text
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_Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks.ipynb → Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks.ipynb
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