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 a series of algorithms that can recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.
- Layers: Deep learning networks have three types of layers: input, hidden, and output.
- Training: The process of teaching a neural network to recognize patterns in data.
Learning Resources
To dive deeper into the basics of deep learning, check out our comprehensive guide on Deep Learning Fundamentals.
Common Applications
- Image Recognition: Identifying objects, faces, and scenes in images.
- Natural Language Processing: Understanding and generating human language.
- Speech Recognition: Transcribing spoken words into text.
Neural Network Diagram
Further Reading
For an in-depth exploration of neural networks and their applications, we recommend the book Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.