Forward Propagation | How a neural network predicts output?

Forward Propagation is a fundamental step in the functioning of neural networks. It involves the transmission of input data through the network's layers to produce an output. Each layer processes the input using weights and activation functions, ultimately generating a prediction. This process is crucial for understanding how neural networks make predictions. Digital Notes for Deep Learning: https://shorturl.at/NGtXg ============================ 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✨ #ForwardPropagation #NeuralNetworks #MachineLearningBasics #PredictionGeneration #DataScience #NeuralNetworkMechanism