Deep Learning

Deep learning (DL) is a collection of algorithms used in machine learning (ML). It is used to model high-level abstractions in data through the use of data model architectures. DL is part of a broad family of methods used for machine learning that are based on learning representations of different types of data sets. Furthermore, deep learning is a more complex model of machine learning that combines other algorithms and combines the outcomes to allow the program to learn further.

• Machine learning is an application of artificial intelligence (AI) that includes algorithms that parse data set, learn from it and then apply what it learned to make information decisions. Furthermore, machine learning gives computers the ability to learn without being explicitly programmed.
• Deep learning is type of machine learning (ML) that structures algorithms in layers to create an artificial neural network (ANN) that can learn and make intelligent decisions on its own. In other words, machine learning (ML) is a superset of deep learning (DL).
• Deep learning is just a subset of machine learning and functions in a similar manner. Both machine learning and deep learning are subsets of artificial intelligence (AI). Furthermore, deep learning has huge data needs but requires little human intervention to function properly.
• Machine learning data representation uses structured data, while deep learning relies on layered structure of algorithms referred to as artificial neural networks (ANN).

Some application areas of deep learning include the following;

• Autonomous cars
• Natural language processing (NLP)
• News aggregation and fake news detection
• Fraud detection
• Entertainment
• Visual assistance
• Chatbots
• Healthcare
• Visual recognition
• Virtual reality (VR)
• Music composition
• Robotics
• Election predictions
• More