Deep learning is a subset of machine learning that involves artificial neural networks with many layers. These networks can learn complex patterns from large amounts of data, making them powerful tools for tasks like image recognition, natural language processing, and more.
Key Concepts
- Neural Networks: The basic building blocks of deep learning, inspired by the human brain.
- Layers: Networks consist of input, hidden, and output layers. Hidden layers enable the model to learn abstract features.
- Backpropagation: A method to train neural networks by adjusting weights based on error rates.
Applications
- Image classification (e.g., CNN tutorials)
- Speech recognition
- Autonomous vehicles
- Game playing (e.g., AlphaGo)
Further Reading
For a deeper dive into neural network architectures, check out our Deep Learning Basics guide.