Neural Networks and the Multilayer Perceptron

40 min

Block 11 — Classification Algorithms
Objective: rigorously define the artificial neuron and layered architecture, understand the backpropagation learning mechanism, learn to configure an MLPClassifier within a pipeline, and decide when a multilayer perceptron is justified on tabular data.
Estimated duration: 65 minutes
Prerequisites: chapters 023 (feature scaling), 029 (fit / predict), 030 (error, loss, metric), 031 (overfitting), 033 (reducing overfitting), 036 (logistic regression)
Associated quizzes: 043.1-neuron to 043.7-tabular-positioning

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This lesson is part of the “Classification Algorithms” module

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