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 layers of interconnected nodes that process and transmit information.
- Layers: Deep learning models consist of multiple layers, including input, hidden, and output layers.
- Activation Functions: These functions help determine whether a neuron should be activated or not, based on the input it receives.
Applications
Deep learning has revolutionized various fields, including:
- Image Recognition: Used in applications like facial recognition, object detection, and medical image analysis.
- Natural Language Processing (NLP): Powers language translation, sentiment analysis, and chatbots.
- Recommender Systems: Enhances user experience by providing personalized recommendations.
Resources
For further reading, check out our comprehensive guide on Deep Learning Basics.
Deep Learning Architecture