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Code - https://github.com/campusx-official/100-days-of-deep-learning/tree/main/day3 Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes A Perceptron is a simple type of artificial neural network algorithm developed by Frank Rosenblatt in 1957. It's the basic unit of a neural network, taking multiple binary inputs and producing a single binary output. It computes a weighted sum of its input, applies an activation function, and produces an output. Perceptron vs. Neuron: Perceptron: Refers specifically to the algorithm developed by Rosenblatt, typically using a step function as the activation. Neuron: A more general term used in the context of biological and artificial neural networks. It encompasses various activation functions beyond the step function. ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at [email protected] 👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science! 💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you! ✨ Hashtags✨ #Perceptron #Neuron #NeuralNetworks #MachineLearning #ArtificialIntelligence #DataScience ⌚Time Stamps⌚ 0:00 Introduction 2:08 What is a Perceptron? 14:30 Neuron Vs Perceptron 22:52 Geometric Intuition 33:53 Code Example 38:04 Outro
