While Model Trains

Read data blog posts.
Carefully handpicked.
Presented 3 at a time.

From both sides now: the math of linear regression

Katherine Bailey

A journey starting from the standard formulation of linear regression, moving on to the probabilistic approach, and then progressing to Bayesian linear regression.

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An Introduction to different Types of Convolutions in Deep Learning

Paul-Louis Pröve

Dilated, transposed, and separable convolutions explained with informative animations.

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How much data should you allocate to training and validation?

Francesco Pochetti

To avoid responding with "that's what Andrew NG said" when asked about the reason behind choosing an 80% training and 20% validation split, consider this explanation.

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