What is deep learning?
Deep learning is a subset of artificial intelligence (AI) and machine learning. It uses both structured and unstructured data for training.
Deep learning uses a layer of the algorithm to create a neural network, which is an artificial replication and structure of the human brain.
The learning is called “deep” because, at each passing level, the neural network rapidly discovers new levels of data.
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A neural network learns through the process of back-propagation.
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Each time the data is trained with a large dataset of inputs, the efficiency is enhanced.
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Deep learning is based on the functionality of the human brain.
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It imitates the human brain’s functionality for managing data and forming patterns for decision making.
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The trained dataset can be interconnected, diverse, and complex.
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When creating deep learning algorithms, developers and engineers configure the number of layers and types of functions that connect each layer’s output to the input of the next layer.
Artificial neural network
Artificial neural networks (ANNs) are computer models inspired by the design and working of the human brain. They are a subset of machine learning algorithms used for various tasks, including classification, regression, pattern recognition, and decision-making.
Applications
Deep learning has proven to be very efficient in tasks like:
- Image captioning
- Voice recognition
- Facial recognition
- Medical imaging
- Language translation
- Self-driving cars
Note: Refer to the following article on neural networks for more information.
