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I have read about LSTM and I know that algorithm takes the value of the previous words and consider it …
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I have a data set X that is composed of mean and standard deviation, this is repeated 5 times, so …
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It is known that we are putting random seeds to ensure the same results are repeated every time we run …
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from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(df, y) X_train = torch.from_numpy(X_train.to_numpy()).float() X_test = torch.from_numpy(X_test.to_numpy()).float() y_test = torch.squeeze(torch.from_numpy(y_test.to_numpy()).float()) …
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I am wondering how I can formate my data, a list of 1000 numeric features, into a shape that my …
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Closed. This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update …
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While training a model to recognize and categorize images with: epochs=2 history = model.fit_generator(train_data_gen, steps_per_epoch=int(np.ceil(total_train / float(BATCH_SIZE))), epochs=epochs, validation_data=val_data_gen, validation_steps=int(np.ceil(total_validation …
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I’m currently learning about how to use neural networks while working on a project of mine. In the project I’m …
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I try to train NN for binary labels, here is my data: Train: {‘0’: 126315, ‘1’: 2915} Val : {‘0’: …
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I have a neural network that is trained successfully based on three metrics. The metrics are: Hamming Loss (mode="multi-label") F1 …
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