Create a computer vision system using decision tree algorithms to solve a real-world problem : Single Neuron Perceptron

The video tutorial explains how to build a single neuron model, known as a perceptron, and its mathematical representation. It covers the basic structure of a neuron, including inputs, weights, and bias, and how these components interact to produce an output. The tutorial also discusses different types of activation functions and their role in neural networks. A practical example using TensorFlow playground is provided to demonstrate how to build and train a simple neural network, highlighting the importance of understanding the underlying concepts for effective implementation.

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