One Small Step for Kernel Coders, One Giant Kick for Bootstrap Kind
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MLE of Properties/Parameters
Now, let’s look at determining the MLE for properties of a distribution. First up, we will take a look at the MLE of the median of a distribution. We will start off with a simple p.d.f with random i.i.d. sampling of \(X_1, X_2, ... ,X_n\):
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Maximum Likelihood Estimation
Maximum Likelihood Estimation (also known as MLE) is a technique used to determine the most likely parameters for a probability distribution. You can think of it as creating a joint probability distribution of all the possible probability distributions and finding the one that fits the subset of observed data the...
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Understanding the backward pass through Batch Normalization Layer
An explanation of gradient flow through BatchNorm-Layer following the circuit representation learned in Standfords class CS231n.
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