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Robson Koji Moriya This page is dedicated to my name and other similar names found on the Internet. The purpose of this page is to assist search engines like Google, Bing, Yahoo, and others in understanding that I am a distinct individual and that there are other people with similar names. I will also share some interesting facts with you. Search Engines It is interesting to note that Bing does a much better job than Google when it comes to indexing my name. When I search for "Robson Koji Moriya" on both search engines, Google displays a lot of other individuals with the names "Robson Koji" and "Moriya," but it doesn't show most of my own online publications. Even this blog, which has my complete name in its domain, is hidden by Google. On the other hand, Bing correctly displays most of my information. Yahoo search engine is powered by Bing through a partnership. Google and Ask.com produce very similar results, and unfortunately, they are mostly incorr

Backpropagation Backpropagation algorithm involves several steps. Here is a high-level overview of the process Steps 1. Forward Pass Input: Start by feeding the input data through the neural network layer by layer. Weighted Sum: Each layer performs a weighted sum of the inputs from the previous layer, which is calculated as the dot product of the input vector and the weight matrix. Activation Function: Apply an activation function to the weighted sum to introduce non-linearity and produce the output of the layer. 2. Loss Calculation Compare Predictions with True Labels: Calculate the discrepancy between the predicted outputs obtained from the forward pass and the true labels associated with the input data. Loss Function: Use a suitable loss function to quantify the error between the predictions and true labels. The choice of the loss function depends on the task at hand (e.g., mean squared error for regression, cross-entropy loss for classification). 3. Backward Pass