Short visual explanations of artificial intelligence concepts, code, and methods delivered to your inbox.
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The bias-variance tradeoff represents the balance between a model's simplicity (bias) and its sensitivity to fluctuations in the training data (variance). Striking the right balance minimizes the total error and achieves the best performanc...
Stochastic gradient descent with momentum uses an exponentially weighted average of past gradients to update the momentum term and the model's parameters at each iteration. It helps the optimizer maintain a more stable direction and speed u...
RMSprop optimizer adjusts the learning rates of each parameter based on the root mean square of the past gradients. It uses a moving average of the squared gradients to normalize the gradient updates and prevent oscillations in optimization...
The writers behind this newsletter.
Present: Director of Machine Learning. Past: Three times Director of Data Science
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