Mean Squared Error loss function and its gradient (derivative) for a batch of inputs [Python Code]
In this post, I show you how to implement the Mean Squared Error (MSE) Loss/Cost function as well as its derivative for Neural…
Read MoreIn this post, I show you how to implement the Mean Squared Error (MSE) Loss/Cost function as well as its derivative for Neural…
Read MoreThe mathematical definition of the Tanh activation function is and its derivative is defined as The Tanh function and its derivative for a…
Read MoreThe mathematical definition of the Softplus activation function is with the derivative defined as , which is actually the Sigmoid function. We have…
Read MoreThe mathematical definition of the Softmax activation function is with the derivative defined as The Softmax function and its derivative for a batch…
Read MoreThe mathematical definition of the Sigmoid activation function is and its derivative is The Sigmoid function and its derivative for a batch of…
Read MoreThe mathematical definition of the ReLU activation function is and its derivative is defined as The ReLU function and its derivative for a…
Read MoreManas SharmaPh.D. researcher at Friedrich-Schiller University Jena, Germany. I’m a physicist specializing in computational material science. I write efficient codes for simulating light-matter…
Read MoreManas SharmaPh.D. researcher at Friedrich-Schiller University Jena, Germany. I’m a physicist specializing in computational material science. I write efficient codes for simulating light-matter…
Read MoreManas SharmaPh.D. researcher at Friedrich-Schiller University Jena, Germany. I’m a physicist specializing in computational material science. I write efficient codes for simulating light-matter…
Read MoreManas SharmaPh.D. researcher at Friedrich-Schiller University Jena, Germany. I’m a physicist specializing in computational material science. I write efficient codes for simulating light-matter…
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