Mutual Information: visual explanations of ML fundamentals. Mutual Information is one of the absolute best tutorial-and-explanation videos about the visual math of basic (small-model) machine learning. includes things like gaussian processes, which, it turns out, neural networks are a special case of. This means that neural networks are actually equivalent to non-parametric models, the weights are simply a reprojection of the training data (kinda obvious in retrospect), and understanding gaussian processes is not optional in understanding how neural networks interpolate between their training data. His video on gaussian processes is wonderful. https://www.youtube.com/watch?v=UBDgSHPxVME—lots of other interesting videos as well https://www.youtube.com/channel/UCCcrR0XBH0aWbdffktUBEdw
Mutual Information: visual explanations of ML fundamentals. Mutual Information is one of the absolute best tutorial-and-explanation videos about the visual math of basic (small-model) machine learning. includes things like gaussian processes, which, it turns out, neural networks are a special case of. This means that neural networks are actually equivalent to non-parametric models, the weights are simply a reprojection of the training data (kinda obvious in retrospect), and understanding gaussian processes is not optional in understanding how neural networks interpolate between their training data. His video on gaussian processes is wonderful. https://www.youtube.com/watch?v=UBDgSHPxVME—lots of other interesting videos as well https://www.youtube.com/channel/UCCcrR0XBH0aWbdffktUBEdw