Deep Learning

Core Idea

Deep Learning is a branch of machine learning that uses neural networks with many layers to analyze complex patterns in large datasets.

Explanation

Deep Learning involves using neural networks with multiple layers (deep neural networks) to process large, complex datasets. These networks learn patterns and hierarchies, driving breakthroughs in image recognition, natural language processing, and autonomous systems. Deep Learning models typically require significant computing power and large datasets for effective training.

Applications/Use Cases

• Image Recognition – Powers facial recognition, medical imaging, and object detection.
• Speech Recognition – Used in voice assistants like Siri and Alexa to interpret spoken language.
• Autonomous Driving – Processes visual and sensory data to allow vehicles to navigate safely.

Related Resources

• TBD

Related People

• Yann LeCun – Pioneer in deep learning, particularly in convolutional neural networks (CNNs) for image processing.
• Geoffrey Hinton – Known as the “Godfather of Deep Learning” for his work on neural networks.

Related Concepts

• Machine Learning – Deep learning is a specialized form of machine learning.
• LLM (Large Language Model) – Uses deep learning to process and generate language.
• Embedding – Deep learning models often use embeddings to represent language or visual data.