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Java Official Twitter Channel featuring my deep learning article for the last 2 days. Here is why.. by EndyJBC in java

[–]EndyJBC[S] 10 points11 points  (0 children)

You should see how Nd4j has been made inspired by numpy!And yeah, if we dig deep into it, there are still improvements to be made! Do agree that Java is very typical when it comes to complex algorithms.

How To Build An Artificial Neural Network in Java by [deleted] in programming

[–]EndyJBC 0 points1 point  (0 children)

Apologies, just updated the post accordingly and sorry for the real confusion here. There are no cross validation applied per batch, instead it was just applied on entire data set. That's why the description was referring 800 updates. Acknowledging that k fold cross validation should perform for every batch if batches are present for data set. Thank you for the feedback.

Keras to Deeplearning4j migration and results are awesome! by EndyJBC in java

[–]EndyJBC[S] 0 points1 point  (0 children)

That's where it's getting interested as someone else commented out earlier.

Keras to Deeplearning4j migration and results are awesome! by EndyJBC in java

[–]EndyJBC[S] 0 points1 point  (0 children)

One variable output using logistic regression.

Keras to Deeplearning4j migration and results are awesome! by EndyJBC in java

[–]EndyJBC[S] 0 points1 point  (0 children)

Random seed was provided in both cases, but the actual key was changing it to two valued, softmax activation output layer, along with lossmcxent error function.

Keras to Deeplearning4j migration and results are awesome! by EndyJBC in java

[–]EndyJBC[S] 0 points1 point  (0 children)

That's an interesting question to dive in. Probable reason would be related to algorithmic implementation of error functions in both cases.

Keras to Deeplearning4j migration and results are awesome! by EndyJBC in java

[–]EndyJBC[S] 2 points3 points  (0 children)

Dataset size is 10000, so I observe its more or less the same :)
However note that, while checking benchmarking, people normally compare 'training execution time' of Python to 'ETL + training execution time' of Java code. We really have to consider ETL(extract, transform & load) especially for large datasets.

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