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A lot of us have heard the term “Artificial Intelligence” being liberally used. Most of us can discern a general idea of what it is from its literal meaning- Artificial meaning something that isn’t natural, in this case being machines and Intelligence being the capacity to make inferences from certain data, ideating, thinking etc. As compared to humans and animals, who are expected to show natural intelligence, AI is the intelligence demonstrated by a machine.

For a layman, his first introduction to the world of AI would usually be through futuristic movies which constantly dabble in this field of technology. For the others, AI is the future.

Machine Learning, which is a relatively unheard term, is in fact closely related to AI. Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. It deals with the pattern recognition and computational theory subset of AI. It focuses on the development of computer programs that can access data and use it learn for themselves. The learning is majorly data or observations based, such that machines are allowed to make inferences on their own, without any constant human interference. Data is fed into the system, the system reads and analyzes the data and produces the required results without following a tailor made program written by a human. It uses methods of statistical analysis to analyze a given data set. A machine is thus given the liberty to “think”.

The basis of Machine Learning is predictive analysis. The system identifies some trends and interesting patterns in a given dataset and hence allows us to predict the behaviour of similar data in the future. It can be classified into two broad categories, namely, supervised and unsupervised learning.

Putting it in simple terms, supervised learning can be compared to when a school teacher gives a student homework. The teacher explains the concept in class and solves certain examples so that the student has a general idea regarding how to approach a given problem and hence can successfully solve the homework. Similarly, when it comes to machines, the computer is presented with example inputs and their desired outputs such that it is able to figure out a general rule mapping the inputs to their outputs.

In unsupervised learning, there are no labels provided in the given dataset, the machine is expected to find out the existing interesting patterns and structure in it. This can be likened to a PhD scholar carrying out her research where she is expected to come up with relevant discoveries from a given dataset.

Classification and clustering are two of the most widely used techniques. In classification, data is separated into labels or classified, and is tackled in a supervised manner, whereas in clustering the input is to be divided into previously unspecified groups and is usually unsupervised in nature.

Machine learning can be seen at work in most software tools that help you in managing your organizational activities. VComply is one such compliance tool which uses machine learning at its very basic level. You get constant alerts and notifications based on your team’s performance and your pre-decided preferences. The computer or machine itself analyses the data and forms conclusions. The machine then notifies the user, with little or no human interaction.

Since Artificial Intelligence is making a rapid foray into today’s world, Machine Learning is the future where computer will be able to work on their own, unaided by humans

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