What is Machine Learning?
Machine learning is a subset of artificial intelligence focused on building systems that can learn from historical data, identify patterns, and make logical decisions with little to no human intervention. It is a data analysis method that automates the building of analytical models through using data that encompasses diverse forms of digital information including numbers, words, clicks and images.
Machine learning basically is a combination of multiple technologies namely artificial intelligence, data analytics, programming, etc. To put it in simple words, machine learning is a science through which you train machines, specifically computers to learn from voluminous data and predict outcomes that can solve a given problem in the best possible.
A brief history of machine learning
You might think that machine learning is a relatively new topic, but no, the concept of machine learning came into the picture in 1950, when Alan Turing (Yes, the one from Imitation Game) published a paper answering the question “Can machines think?”
Why is Machine Learning Important?
Machine learning is growing in importance due to increasingly enormous volumes and variety of data, the access and affordability of computational power, and the availability of high speed Internet. These digital transformation factors make it possible for one to rapidly and automatically develop models that can quickly and accurately analyze extraordinarily large and complex data sets.
The practical applications of machine learning drive business results which can dramatically affect a company’s bottom line. New techniques in the field are evolving rapidly and expanded the application of ML to nearly limitless possibilities. Industries that depend on vast quantities of data—and need a system to analyze it efficiently and accurately, have embraced ML as the best way to build models, strategize, and plan.
Which Language is best for Machine Learning?
What Makes Machine Learning So Useful?
Machine learning technology is now necessarily new; machine learning algorithms have existed for years, but machine learning processes have recently taken prominence due to several important technological improvements, including:
• Wider access to large volumes and varieties of data, especially the development and ubiquity of “big data”.
• Much more affordable data storage solutions, which helped make big data sets available to more organizations and for a much wider variety of applications.
• Increasing processing power that allows computers and specifically AI applications to complete calculations much faster than ever before.
The machines of the current era are nothing like what existed a few decades ago. These machines are smart and trained on massive datasets, thereby minimizing the chances of errors. The machine learning algorithms these days are highly advanced. Although most of these work on specific data models, the advantage with machine learning is that as soon as the models get exposed to new patterns present in the data, these algorithms smoothly adapt to it and simplify things for the users.
To get the most value from machine learning, you have to know how to pair the best algorithms with the right tools and processes. Get in touch with Realxposure’s Expert team to learn more!
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