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. Each layer performs a specific function in the learning process.
- Backpropagation: This algorithm helps adjust the weights of the neurons in a neural network to improve the accuracy of predictions.
Applications
Deep learning has revolutionized various fields, including:
- Image Recognition: Identifying objects and patterns in images, such as facial recognition and medical imaging.
- Natural Language Processing (NLP): Understanding and generating human language, enabling applications like chatbots and machine translation.
- Recommender Systems: Personalizing recommendations for users based on their preferences and behavior.
Resources
For further reading on deep learning, check out our Deep Learning Tutorial.
Deep Learning Architecture