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How Deep Learning Works | IABAC

Deep learning works by using artificial neural networks with multiple layers that process data step by step. Each layer learns patterns from the data, improving accuracy over time through training methods like forward propagation and backpropagation.

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How Deep Learning Works | IABAC

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  1. How Deep Learning Works iabac.org

  2. What Is Deep Learning? Deep learning is a part of machine learning (ML), which is a branch of artificial intelligence (AI). It uses artificial neural networks that work like the human brain. These networks help computers learn patterns and make decisions with little human help. Example: Showing thousands of cat images → the system learns what a cat looks like automatically. iabac.org

  3. Structure of a Deep Learning Model A deep learning model has layers that process information step by step: Input Layer: Takes in data (like an image or sound). Hidden Layers: Find patterns and relationships in the data. Output Layer: Gives the final result (like “this is a cat”). More hidden layers = deeper learning. iabac.org

  4. How Deep Learning Learns The learning process happens in two main steps: 1.Forw ard Propagation: Data moves through the network and makes a prediction. 2.Backpropagation: The model checks errors and adjusts its internal settings (weights). This process repeats until the model becomes accurate. iabac.org

  5. Why Deep Learning Matters Deep learning powers many everyday tools and systems: Voice assistants (Siri, Alexa) Face recognition Self-driving cars Chatbots and recommendation systems It helps machines understand and interact with the world more like humans do. iabac.org

  6. Thank You visit: www.iabac.org

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