Deep Learning

Deep learning is a subset of machine learning that uses artificial neural networks to analyze complex patterns and data structures. It powers AI applications like speech recognition, computer vision, and autonomous systems by mimicking the human brain’s ability to learn from experience. Deep learning models, such as convolutional neural networks (CNNs) and transformers, process large datasets to deliver highly accurate predictions.

Key Features:

• Multi-layered neural networks – Enables high-level abstraction and pattern recognition.

• Feature learning – Automatically detects key characteristics from data.

• Scalability – Handles massive datasets efficiently.

• Self-improving models – Learns continuously from new data.

Best Use Cases:

• Speech recognition (e.g., Siri, Google Assistant).

• Computer vision for facial recognition and object detection.

• Autonomous vehicles for real-time decision-making.

• Healthcare AI for disease prediction and diagnosis.

• Financial forecasting and fraud detection.