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: Mimic the human brain's ability to recognize patterns.
  • Layers: Composed of neurons that process and pass information.
  • Backpropagation: Adjusts the weights of the neurons to improve accuracy.

Applications

  • Image Recognition: Identifying objects in images, such as in self-driving cars.
  • Natural Language Processing: Understanding and generating human language, like chatbots.
  • Recommender Systems: Personalizing content, such as movie or product recommendations.

Resources

For further reading, check out our Deep Learning Course.

Learning Path

  1. Understanding Neural Networks
  2. Implementing Deep Learning Models
  3. Practical Applications of Deep Learning

Deep Learning Architecture