100 Days of Deep Learning - Perceptron Trick | How to train a Perceptron | Perceptron Part 2 | Deep Learning Full Course

Code - https://github.com/campusx-official/100-days-of-deep-learning/tree/main/day4 Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes Training a Perceptron involves adjusting its weights to correctly classify input data. The process typically follows these steps: Initialize Weights: Set initial weights randomly. Forward Pass: Compute the weighted sum of inputs and pass it through an activation function. Calculate Error: Compare the predicted output with the actual target. Update Weights: Adjust weights based on the error using a learning rate and the gradient descent algorithm. Repeat: Iterate through the dataset multiple times (epochs) until the model converges. ============================ 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✨ #PerceptronTraining #NeuralNetworks #MachineLearning #GradientDescent #DataScience #PerceptronAlgorithm ⌚Time Stamps⌚ 00:00 - Intro 01:20 - Perceptron Trick 10:35 - How to Label regions? 13:25 - Transformations 25:00 - Coding the Algorithm 36:00 - Simplified Algorithm 41:20 - Code Demo 51:16 - Outro