You must have heard about the names like Alexa, Siri, Cortana in your surrounding more often than the name of your colleagues. Artificial intelligence and machine learning together are converting the part of the fictional future into a reality. The revolutionary changes in past few years bring the automation and smart solution for performing complex operations.

With the introduction of cloud computing, it has become easy and quick to develop applications for the AI or ML due to offered stupendous resources. The infrastructure, platform, storage, software etc., based services available at any time and can be accessed from anywhere with supported devices. Recently Amazon has offered an AI and Ml based virtual voice assistance feature named Alexa, which can be implemented in supported applications and devices with its available APIs and modules transforming them into smart applications or smart devices. It was first successfully integrated with the speakers’ named echo.

Similarly, the ML-based automated chatbot has become very popular with its expanded use in various applications such as site, messenger, or other works. Websites are implementing such as Natural Language Processing(NLP) based bots for attracting more qualified leads and providing instant solutions to the end users in chat. The platform such as aws Lex allows you to develop a voice or text-based automated chat assistance for your application. Without machine learning, it would not have been that easy as it requires a tremendous amount of time and effort to develop such applications.

Introduction to machine learning is the outcome of the pattern recognition and computational knowledge of artificial intelligence. It comprises the implementation of the statistical and mathematical techniques to provide a system with the ability to learn from the data and make predictions on submitted data. It automatically creates algorithm model according to the given input for predicting the actual outcome.

The vast area of ML and AI covers the applications like email spam filtering, cybersecurity protection, face or speech recognition etc.

Big companies always predict their future with multiple data set for a better throughput and loss prevention. In share market companies predicts for the future stock by performing the computational and statistical operations on the previous and present data. Depending upon the forecast companies sell or buy their shares delivering a profitable statement for the organisation.

In industries, various operations are hastened with the help of computational analytics. The supply chain management of an organisation predicts for the future stock of the product so that the estimation for the supply and manufacturing stock can be aligned efficiently in the inventory for further distribution.

In large manufacturing plant where the data is collected from the IoT based devices such as a programmable logic controller(PLC) used in the refineries. The data obtained from the various apparatus such as a level transmitter, sensors, mass flow metres etc., are used to acknowledge the overall performance of the plant. The predictions based on these supply chain assets extends the life and performance of these devices. The data collected from these SCADA and other systems are stored for years and on executing ML operations for analysing such massive data determine the factors or obstacles involved in the journey.

Apart from the industries, the online marketing has adopted the prediction based system very precisely for analysing the customers’ search. The e-commerce platforms are very efficiently using the ML to predict the products which a user can buy in the future.

We can judge from the above examples that how ML has changed the traditional ways of performing complex works. The outcomes observed from its implementation are much more extraordinary than someone’s thinking as it goes beyond the human’s capability.

By lexutor