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Dear Learners, welcome to the video. In this video we discuss Multilayer perceptrons,(MLPs) are a type of artificial neural network (ANN) that are used to model complex patterns in data. MLPs are composed of multiple layers of processing units, or neurons, that are interconnected in a feed-forward manner. The input layer receives the input data, and each subsequent layer transforms the data until the output layer produces the desired output.
A multi-layer perceptron contains one input layer with one neuron (or node) for each input, one output layer with one node for each output, and any number of hidden layers with any number of nodes on each hidden layer.

Neural networks:
Neural networks, also called artificial neural networks (ANN), are systems based on the biological neural networks constituting animal brains. Neural networks are one of the most popular machine learning algorithms owing to their computational power. Just as the neurons in our brains can learn from past experiences, neural networks can also learn from data to provide information in the form of predictions.

Topics Covered:
00:00:00 Introduction to Neural Network
00:00:10 Why use Neural Networks?
00:14:30 Where do we use Neural Networks?
00:28:30 Multilayer Perceptron
00:28:46 Practical Demonstraion

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