About
Deep Learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. It is also known as deep neural learning or deep neural network.
What is Deep Learning?
Deep learning involves the use of large neural networks – structures inspired by the human brain – to automatically learn and make decisions from data. These networks are called artificial neural networks (ANNs).
Key Components of Deep Learning
- Neural Networks: Composed of layers of interconnected nodes or neurons, where each layer performs specific functions.
- Weights and Biases: Adjusted during training to improve the model's accuracy.
- Activation Functions: Determine the output of a neural network node, adding non-linearity to the model.
Why is Deep Learning Important?
Deep learning drives many artificial intelligence (AI) applications and services that improve automation, performing analytical and physical tasks without human intervention.
Applications of Deep Learning
- Image and Voice Recognition: Powers applications like virtual assistants and face recognition systems.
- Natural Language Processing (NLP): Used in language translation, sentiment analysis, and chatbots.
- Self-driving Cars: Enables autonomous vehicles to recognize the space around them.
- Medical Diagnosis: Assists in identifying diseases from medical imagery.