Deep learning is a subfield of machine learning that focuses on algorithms inspired by the structure and function of the brain, called artificial neural networks. These networks learn to perform tasks by considering examples, typically without being explicitly programmed.
Key Concepts
- Neural Networks: Composed of layers (input, hidden, output) that process data hierarchically.
- Deep Learning vs. Machine Learning: Unlike traditional ML, deep learning automatically extracts features from raw data through multiple layers.
- Common Architectures
- Convolutional Neural Networks (CNNs) 🖼️
- Recurrent Neural Networks (RNNs) ⏳
- Transformers (Attention-based models) 🔍
Applications
- 🧠 Computer Vision: Image classification, object detection, and segmentation.
- 🗣️ Natural Language Processing (NLP): Sentiment analysis, machine translation, and chatbots.
- 🎧 Speech Recognition: Converting audio to text (e.g., voice assistants).
- 🚗 Autonomous Driving: Real-time object tracking and decision-making.
Learning Resources
For hands-on tutorials:
→ Explore Deep Learning Tutorials
For a deeper dive into advantages:
→ Deep Learning Advantages