Machine Learning

As you know, human learns from their experiences, and their decisions are based on past experience whereas machine needs to be explicitly programmed to perform any sort of task.Computers responds fast and they are better at math right now but actually it can not deal with human language unless given an intense algorithms to parse and make sense out of it. "Machine learning is the art that gives computers the ability to learn or predict without being explicitly programmed based on past data".

It provides cooked methods to programmers which can be used to process natural language.In commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to "produce reliable, repeatable decisions and results" and uncover "hidden insights" through learning from historical relationships and trends in the data.

In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.

Examples of Machine Learning:
Google Search Engine, Facebook Photo Tagging,Netflix product Recommendations, Voice Assistants in Market(like Apple Siri, MS Cortana, OK Google) etc...
Customers visit prediction at Super Market:
Let see, we got past months data from Super market to know whether number of customer's going to increase or decrease during upcoming month.We can run past data through algorithmic predictive model and be able to analyze whether there is increase or decrease in coming month and if prediction warns about decrease in customer base, mouth watering offer can sent over to customers phone or email to stay strong with business.