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I am trying to build a simple multi layer perceptron Neural Network in Java, but apparently my calculations are off. I am looking for a beginner-level tutorial which can help me to understand how to properly calculate forward and backward pass, preferably with examples.

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One of articles which helped me a lot is : A Step by Step Backpropagation Example by Matt Mazur. It covers forward and backward pass of MLP. I hope that helps.

Another great source is http://www.deeplearningbook.org/

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Apart the mentioned resources, this also might be of help: MLP Java example. It's from the University of Sydney and includes theory and a Java implementation.

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You can follow this tutorial Neural Network: A Complete Beginners Guide from Scratch. It's covered the very basics and also shared the code.

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