Backpropagation

Backpropagation is the core algorithm that makes neural networks trainable. The forward pass tells the model what prediction it currently makes. Backpropagation tells the model how each weight contributed to the error so the optimizer can update those weights in the right direction. People often hear that backpropagation is “just the chain rule,” which is true but not especially helpful. The useful mental model is this: the forward pass computes values the backward pass computes sensitivities each node only needs its own local derivative the full gradient is built by multiplying those local derivatives along the path If that sounds abstract, it becomes much clearer once you look at one neuron first and then scale up. ...

Introduction Into to deep learning Intelligence: The ability to process information and use it for future decision-making. Artificial Intelligence (AI): Empowering computers with the ability to process information and make decisions. Machine Learning (ML): A subset of AI focused on teaching computers to learn from data. Deep Learning (DL): A subset of ML utilizing neural networks to process raw data and inform decisions. Why Deep Learning Now? The recent surge in deep learning’s capabilities can be attributed to three key factors: ...