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➡️ Machine Learning from Scratch, part 42: why GPU and not CPU. A neural network spends almost all of its time multiplying numbers and adding them up. In every layer each neuron receives the whole input vector, multiplies each number by its own weight and adds them up, so with the weights of all neurons as the rows of one table, the layer becomes one matrix times the input vector. In training a whole mini batch goes in at once, every layer becomes a matrix times a matrix, and the backward pass f
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decision tree is a machine-learning model that makes predictions by asking a series of questions. Each answer sends it down a different path until it reaches a prediction. #data #machinelearning #algorithm #ai #learnontiktok
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