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How AI, Machine Learning and Deep Learning are Differed
- July 27, 2018
- Posted by: Admin
- Category: Blogs, Business Intelligence, Internet of Things (IoT)
Nowadays, AI is all around us. Google exemplifies this by utilizing Machine Learning within Gmail to filter spam messages. Netflix and Amazon also utilize Deep Learning to predict your next movie or purchase. You might be hearing these terms appear more frequently and it would make sense due to the advent of rapid Big Data and analytics growth in the industrial and business workforce.
Alright. You’ve hear these buzzwords consistently enough to peak your interest – but what is the real meaning of Artificial Intelligence, Machine Learning, and Deep Learning?
Artificial Intelligence (AI)
John McCarthy first coined the term ‘Artificial Intelligence’ in 1956 but AI has turned out to be more famous today due to advance algorithms and enhancements in computing power and capacity. The definition of AI can be broad – it can be used for development, understanding languages, recognizing items and sounds, learning, and even problem solving.
Read More : How Is AI Integrated With Fleet Management?
While Hollywood pictures and sci-fi books have long represented AI as maniacal robots, modern advancements in AI technologies aren’t frightening. Rather, the development of AI can now give numerous advantages to any industry (retail, health care, and more).
Machine Learning (ML)
Machine Learning is a subset of Artificial Intelligence and is a rising development in the field of AI: empowering picture recognition, Natural Language Processing (NLP), and other transformative elements.
Machine learning can be used for operations such as risk analysis, fraud prevention and enlightening medical science. Furthermore, Machine Learning can help shoppers and by use of navigation (Siri, Alexa, etc.) – amongst countless other real-world ML applications.
Deep Learning is another subfield of machine learning and is inspired by the structure and function of the brain, specifically Artificial Neural Networks (ANNs).
According to “Andrew Ng”
“for most flavors of the old generations of learning algorithms … performance will plateau. … deep learning … is the first class of algorithms … that is scalable. … performance just keeps getting better as you feed them more data.”
Source: Slide by Andrew Ng.