Machine Learning is the subsidiary of AI that uses different data analysis and algorithms to impersonate human’s way of learning and ultimately showing more accuracy. Basically; it’s a tool to sort and analyze enormous amount of clustered data, categorized it and predict its most accurate outcome.  The term “Machine Learning” was first used by an IBM professional Arthur Samuel in his research paper; he used this algorithm to feed a computer about the game of Checkers, which produced unbelievable results.
 With respect to its working module, Machine Learning is classified into four different types which are supervised, unsupervised, semi-supervised and reinforcement. It’s obvious with their names that they’re discerned on the basis of how much human intervention they need to produce desired results.
Now the question is what exactly Machine Learning can do? Well maybe without knowing it, we all have experienced it’s uses in our daily life internet surfing. Below are some practical usages of the tool,
 You must’ve wondered at least once in your life, that how come Facebook and Instagram are showing you products that you were just thinking of purchasing. Its because these social media platforms use Machine Learning algorithms to analyze your activities, which means if you’ve ever just liked the picture of anything which shows your even minor of interest in that thing. Then it’s not so difficult for the algorithm to capture it and feed it in its storage. This technique has been utilized to its fullest potential by e commerce industry in order to deliver relevant product to the potential buyer. That’s why most of the time, you can easily find the product you’re looking for in your recommendation section.
You Tube and Facebook also extensively uses this tool to recommend you exact content as per your interest.
 Machine Learning is capable of detecting fraud by gathering all the previous data of the scammers, its mostly use by the banks and corporations that directly or indirectly involves consumer’s money e.g., trading. Immediately catching fraud emails and phone calls is one of the features which have largely benefited the finance industry. The module is also widely regarded as the best tool for predicting business investment outcomes based on the data analysis of the market.
Fitness bands and watches that you normally wear to keep track of your steps and heart rate etc. relies on this algorithm in order to give you an accurate health assessment. Moreover, Machine Learning is noticeably stepping up in the health care industry, as it’s now allowing specialists to perfectly analyze patient’s condition based on his or her medical history.  Medical report analysis through Machine Learning software like Computer aided Detection (CaD) which helps radiologists in diagnosing X rays and MRI results. Thus, promoting success ratio in treating vulnerable diseases.
Connecting to the Clients:
ML data processing factor enables various companies to connect with its potential clients. Like, carpooling applications uses this tool to offer you a perfect ride. Similarly, dating apps provides match making among its users using these software which analyzes nature of all users and then provides results accordingly. ATS software is the best example in this regard, it takes off half the burden from the shoulders of HR and filters out the best few applications out of the thousands. So that company can meet the most suitable candidate.
 With all of its distinguished qualities, no doubt ML is the most pivotal tool for the governments. As gigantic amount of highly complexed data has to be categorized and to be kept in the records. ML software is the automated choice for these kinds of tasks. Plus, it significantly helps concerned authorities to introduce and implement new policies as per requirements due to the systematic analysis of the categorized data.
Simply there is no stoppage to what ML is actually capable of doing, as it has adequately adapted human’s way of doing things. Although the name is not new, but its capability of evolving itself with time, has made it expand to all industries within no time. With most of the human jobs are cease to exist now, still data engineers are required to supervise these tools. But in near future, ML is gonna perform to its fullest extent on its own and that’s a sure thing.