AI, ML, or DL – learn what it means

AI essentially works to develop machines that are self-reliant and can think and act like humans. Examples of AI are machine translation such as Google Translate, speech recognition apps such as Google Assistant or Siri, and AI robots such as Aibo and Sophia. ML looks to solve business problems through predictive models built on analytics and computer models. The work of a machine learning engineer is seen in sales forecasting, stock price predictions, and banking fraud analysis, among others. A subset of ML, DL works with artificial neural networks employing algorithms inspired by the structure and working of the human brain. DL algorithms can work with huge amounts of both structured and unstructured data; ML, in comparison, typically requires structured data. Use cases include the detection of cancerous tumors and other objects and the coloring of images.