Machine Learning is a branch of Artificial Intelligence that teaches computers to complete tasks that previously could have only been done by a human being. To give you a rough idea, take a look at self-driving cars, real-time speech translation, and traffic forecasting – these are all applications of artificial intelligence and its capabilities.  

Firstly, it’s important to understand that Machine Learning is a core sub-area of Artificial Intelligence – it is a method of data analysis that automates analytical model building. In simple words, it is the process of teaching a computer system to accurately make predictions based on data it is given. The objective is to get the system to automatically learn from the data, identify patterns, make decisions, and adjust actions accordingly with minimal human assistance.  

With the increase in readily available data, cheap and powerful computational processing, and affordable data storage, the demand for and importance of Machine Learning has also rocketed. As a technology, its automated processes help analyze huge sums of data, ultimately easing the tasks of data scientists. It has changed the way of prepping, extracting, and interpreting data by replacing the traditional statistical procedures with adding automation sets of generic methods.  

By producing accurate results and analyses through the development of efficient algorithms and data-driven models with real-time processing, Machine Learning has enabled computer science, statistics, as well as other emerging applications, to propel forward in their respective industries.

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