Multi Layer Perceptron | MLP Intuition
Channel: CampusX
Date: 2022-03-01

A Multi-Layer Perceptron (MLP) is a type of artificial neural network characterized by its multiple layers of nodes (neurons). It consists of an input layer, one or more hidden layers, and an output layer. Each connection between nodes is associated with a weight, and each node applies an activation function to the weighted sum of its inputs. MLPs are trained using algorithms like backpropagation to learn and make predictions.

Digital Notes for Deep Learning: https://shorturl.at/NGtXg

Tensorflow Playground - https://playground.tensorflow.org/

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#MLP #MultiLayerPerceptron #NeuralNetworks #DeepLearning #ArtificialIntelligence #DataScience #machinelearning 

⌚Time Stamps⌚

00:00 - Intro
01:28 - The problem
02:42 - Perceptron with Sigmoid
23:56 - Adding nodes in hidden layer
26:58 - Adding nodes in input
28:50 - Adding nodes in output node
29:53 - Deep Neural Network
31:53 - TF Playground Demo
37:21 - Outro