🧠 Going back to the fundamentals of deep learning — Backpropagation, the algorithm that teaches neural networks how to learn from their mistakes. At its core, backpropagation is how models like GPT, Claude, and Gemini actually learn. It systematically adjusts internal parameters, weights and biases, to minimize prediction errors. Check out the thread for the full breakdown 👇 📅 Want to join live? Register now for the upcoming Agentic AI Bootcamp happening on Nov 25th. Don’t miss your chance to build, test, and evaluate intelligent agents! hubs.la/Q03Rz5tc0 #DeepLearning #Backpropagation #NeuralNetworks #MachineLearning #AI #DeepLearningBasics #GradientDescent #ArtificialIntelligence #MLAlgorithms #DataScience

3. Neurons are arranged in layers, forming a network. Each layer builds on the previous one, extracting increasingly complex features from the data. Imagine the team discussing their findings, refining their understanding of the animal. #LayeredLearning #DeepLearningBasics

2. Neural networks in deep learning are like interconnected webs. They process information layer by layer, gradually extracting more intricate features from the data. Think of stacking building blocks - each layer builds on the knowledge from the previous one. #NeuralNetworks #DeepLearningBasics

2. Neural networks in deep learning are like interconnected webs. They process information layer by layer, gradually extracting more intricate features from the data. Think of stacking building blocks - each layer builds on the knowledge from the previous one. #NeuralNetworks #DeepLearningBasics

Whats the difference between #artificial and #biological Neurons again? #deeplearningbasics #devfestka16 @SAPNextGen