What is an example of deep learning?
What is an example of deep learning?
Deep learning is a sub-branch of AI and ML that follow the workings of the human brain for processing the datasets and making efficient decision making. Practical examples of deep learning are Virtual assistants, vision for driverless cars, money laundering, face recognition and many more.
What is deep learning vs machine learning?
Deep learning is a type of machine learning, which is a subset of artificial intelligence. Machine learning is about computers being able to think and act with less human intervention; deep learning is about computers learning to think using structures modeled on the human brain.
What is deep learning and how does it work?
Deep learning can be considered as a subset of machine learning. It is a field that is based on learning and improving on its own by examining computer algorithms. While machine learning uses simpler concepts, deep learning works with artificial neural networks, which are designed to imitate how humans think and learn.
Is deep learning and AI same?
AI means getting a computer to mimic human behavior in some way. Deep learning, meanwhile, is a subset of machine learning that enables computers to solve more complex problems.
What is the purpose of deep learning?
Deep learning eliminates some of data pre-processing that is typically involved with machine learning. These algorithms can ingest and process unstructured data, like text and images, and it automates feature extraction, removing some of the dependency on human experts.
Who is the father of machine learning?
Geoffrey Hinton
| Geoffrey Hinton CC FRS FRSC | |
|---|---|
| Scientific career | |
| Fields | Machine learning Neural networks Artificial intelligence Cognitive science Object recognition |
| Institutions | University of Toronto Google Carnegie Mellon University University College London University of California, San Diego |
What is deep learning Good For?
One of the main advantages of deep learning lies in being able to solve complex problems that require discovering hidden patterns in the data and/or a deep understanding of intricate relationships between a large number of interdependent variables.
Why do we need deep learning?
Deep learning applications are used in industries from automated driving to medical devices. Automated Driving: Automotive researchers are using deep learning to automatically detect objects such as stop signs and traffic lights. In addition, deep learning is used to detect pedestrians, which helps decrease accidents.