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A brief introduction of ML and why it is important

Introduction

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model of sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task.

Machine learning algorithms are used in a wide variety of applications, such as email filtering, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers.



Applications of ML

Image recognition is one of the main advances in artificial intelligent algorithms. Facebook can detect your face, your friend’s face, and probably even your dog, and then assign the appropriate name tag!

Speech recognition is a very fun and interesting application of deep learning. Speech is one of those natural steps towards interacting with technology since we can speak faster than we type, and it is the natural way of communicating.

With the advent of Siri, Alexa, Google Home and others, many companies across the world are using machine learning and deep learning to take in vast amounts of speech data to tease out the nuances in sound.

Recommendation systems are a third set of use cases for machine learning. These applications have been the bread and butter for many companies. When we talk about recommendation systems, we are referring to the targeted advertising on your Facebook page, the recommended products to buy on Amazon, and even the recommended movies or shows to watch on Netflix.

These systems are powered by machine learning algorithms that have detected nuances in human behavior — whether it be purchasing food or watching the last season of The Office. Moreover, these systems have not only proven to work but are now the backbone to a lot of dollars spent on advertising and marketing. Whatever ad you click or how long you spend watching a show are small pieces to the larger algorithm that is running these companies recommendation systems.