So, it’s been a while. The past months of my life have been an absolute whirlwind to say the least and updating this site has just not managed to squeeze … Continue reading Bias and Variance and Mean Squared Error
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So, it’s been a while. The past months of my life have been an absolute whirlwind to say the least and updating this site has just not managed to squeeze … Continue reading Bias and Variance and Mean Squared Error
First things first. Technically, I should have written about this before Gradient Descent as Least Squares was the original technique used to find the optimal equation of a linear model … Continue reading Least Squares Regression and the Sum of Squared Residuals
First thing I noticed while writing this article is the red underline on convolutional – which really should not be there by now. Convolutional Neural Networks (or CNN’s) are a … Continue reading Convolutional Neural Networks
To start off, all three of the above are the same. A Neural Network ‘learns’ by means of its optimizer, and all optimizers are versions of and different implementations of … Continue reading Gradient Descent, Optimizers, and How a Neural Network ‘Learns’
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Now here is where things are starting to get amped up. Artificial Neural Networks are the most basic of Neural Network models, implementing layers of artificial neurons (read about them … Continue reading Artificial Neural Networks