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8 Factors Shaping the future of big data, AI & Machine learning

Our Future is Artificial Intelligence (AI), this word has huge impact on technology. Day by day larger IT companies are showing keen interest on developing Artificial Intelligence, Machine learning big data technologies. These three things are interrelated because we generate large number of data every second, to control this big data generation we have started developing Machine learning algorithms. AI is a subset of Machine learning. We feed data set to machine that creates an intelligent machines to help human beings. Let us know the factors that are shaping big data, Machine learning and Artificial Intelligence.Big data, AI & Machine learning Image

Data mining playing an important role:

As we know that we generate 1.7MB data every second that’s a huge. We should control data generation so most of the tech experts have developed data mining and data cleaning methods. To do this experts have developed many machine learning algorithms such as cluster, classification, regression and many more.


Data platforms for business growth:

Digital marketing businesses already using these platforms, but now a day other businesses also started working on this platform. They know that using this platform they are enabling to serve their customers better. Uber is a great example to serve their customer and grow their business.


Using 5G data has greater impact on Machine Learning:

Data speed, connectivity and usage are the major factors of using 5G data. This will help in growth of business and along with faster transmission of data using sensor IoT capabilities. Office work become less repetitive as machine learning picks up the slacks.


Unsupervised machine learning process:

Working with supervised machine learning algorithm is a normal. Supervised machine learning algorithms work on using labelled data and structure whereas unsupervised algorithm uses the same technique but with unlabeled data. While working with unsupervised algorithms accuracy level is less compare to supervised algorithms. But using mapped application you can get accurate outcomes.


Internal data platforms are become essential for growth and innovation:

Companies like Lyft and BMW work on internal data platform to create Machines that produce the better result. You need robust, hugely scalable platform that will provide all the workflow.


Next generation computing architecture:

Computing Architecture is a prototype means set of rules and methods that helps user to work on functionality and implementation of computer system. IBM has come up with developing cloud computing architecture to merge components and subcomponents to produce elastic machines.


Low cost internet and data scientists’ method:

Many tele companies providing large number of data plan for lower cost. This is one of the major causes to generate large number of data. We access data on FACEBOOK, GOOGLE, YOU TUBE And INSTAGRAM. To control these much data generation, data scientists have come up with ideas like data cleaning and data mining methods.


Important of capturing and computing real time data:

This is the process used for defining, manipulate, retrieve and transfer data in data management system. There are large number of advantages of computing real time data such as agility, improve in policies, governances and data security.


Insights:

From this article you may get few information about how big data, machine learning and AI are interrelated. To control data we use machine learning algorithms and these algorithms create Artificial Intelligence such as Alexa and Sophia.

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