Deep learning is a subset of machine learning that structures algorithms in layers to create an "artificial neural network" that can learn and make intelligent decisions on its own.

Key Concepts

  • Neural Networks: Inspired by the human brain, these networks are composed of interconnected nodes or "neurons" that process information.
  • Layers: Networks are structured in layers, with input, hidden, and output layers.
  • Backpropagation: This is a method used to train neural networks, adjusting the weights of the connections between neurons based on the error rate.

Applications

  • Image Recognition: Deep learning is used to identify objects in images, such as identifying cats in photos.
  • Natural Language Processing (NLP): It helps in understanding and generating human language, making it possible for machines to translate and understand text.
  • Medical Diagnosis: Deep learning models can analyze medical images to help diagnose diseases like cancer.

Further Reading

For more information on deep learning techniques, check out our comprehensive guide on Machine Learning Basics.

Resources

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