Deep learning is a subset of machine learning that involves artificial neural networks with many layers. These networks are designed to mimic the human brain's ability to process complex patterns and make decisions. 🤖
Key Concepts
- Neural Networks: The building blocks of deep learning, consisting of interconnected nodes (neurons) organized in layers.
- Training Process: Involves feeding data through the network, adjusting weights via backpropagation, and minimizing errors.
- Optimization Algorithms: Techniques like gradient descent and Adam optimizer help improve model performance.
Applications
- Computer Vision: Used in image recognition, object detection, and video analysis.
- Natural Language Processing (NLP): Powers chatbots, translation tools, and text summarization.
- Autonomous Systems: Applied in self-driving cars and robotics for real-time decision-making.
For more details on related topics, check out our Machine Learning Basics guide.