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, neural networks are composed of interconnected nodes or "neurons" that work together to process information.
- Layers: Deep learning models consist of multiple layers, including input, hidden, and output layers, which help the network learn and make predictions.
- Backpropagation: This algorithm helps adjust the weights of the neurons in the network, allowing the model to improve its predictions over time.
Applications
Deep learning has been applied to a wide range of fields, including:
- Image Recognition: Identifying objects, faces, and scenes in images.
- Natural Language Processing: Understanding and generating human language.
- Recommender Systems: Personalizing recommendations for users based on their preferences and behavior.
Resources
For more information on deep learning, you can explore the following resources:
Deep Learning Architecture