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Issue with numpy dependency when building docker image

I am trying to create a Sagemaker endpoint for model inference using the Build your own algorithm container (https://sagemaker-examples.readthedocs.io/en/latest/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.html) but am having an issue when installing Numpy in the creation of the image. We've already previously have gotten it to…

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non-broadcastable output operand with shape (5377,1) doesn't match the broadcast shape (5377,15) – Artificial Intelligence

When I want to transform back to original form by using inverse_transform , I get the following error: X_train = [] y_train = [] for i in range(120, data_training.shape[0]): X_train.append(data_training[i-120:i]) y_train.append(data_training[i,0]) X_train , y_train = np.array(X_train) , np.array(y_train) X_train.shape ,…

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