The Future Of Machine Learning: Beyond Our Scope Of Imagination

This is the era when the machines know much about us especially, “what we are looking for.” Each shopping website, entertainment website, etc offers plentiful personalized recommendations to us to choose from. Wanna know how all this is happening? Well, the answer is machine learning. And undoubtedly we are liking it so much this itself declares that it will stay for the long run surely. In fact, this is just a primitive age of machines, while the future of machines is enormous and is beyond our scope of imagination. Hence we can say the future of machine learning is going to be very bright. But to better understand its future scope let’s learn its brief introduction first.

What Is Machine Learning?

Machine learning is a subset of artificial intelligence (AI) that offers systems with the ability to automatically learn and grow from experience even without any explicit programming on it. Moreover, the field focuses on the development of computer programs that can access data and further use it to learn for themselves..

Well, this process of learning machine learning becomes effective with observations or data, such as examples, instruction, or direct experience, to look for patterns in data to make better decisions in the future based on the samples that we provide. Most importantly, this application AI enables the computers to learn automatically even without human assistance & intervention and later adjust actions accordingly.

 Machine Learning Algorithms​  

In simple words, programs (math and logic) that adjust themselves to perform better as they are exposed to more data are the Algorithms of Machine Learning. Commonly, Machine Learning Algorithms are divided into three categories, according to their purposes. They are:

a. Supervised Machine Learning Algorithms

    In this algorithm, every instance of the dataset comprises both input attributes and expected output. To find out the better predictions, the system is allowed to take any kind of data as input like the pixels of an image, values of a database row, or even an audio frequency histogram. 

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b. Unsupervised Machine Learning Algorithms

      Unlike Supervised Machine Learning Algorithms, here the dataset does not comprehend 
      any expected output. based on the typical characteristics of the input data, the system detects            patterns. And, the machine then groups similar data samples and identify different clusters                within the data for more effective results.

C. Reinforcement Machine Learning Algorithms

     Well, this learning algorithm works amid the interaction between the environment and the                   system.There are two ways results are obtained here, one is trial and error method 

     while the other one is when the system produces results based on knowledge gained 

     from the environment. 

Machine Learning Applications

a. In Healthcare

    Like every domain, now machine learning is growing scopes in healthcare as well. For example, Computer vision in healthcare. Yes, it is an active healthcare application for ML Microsoft’s Inner-eye initiative that started in 2010 and is now working on an image diagnostic tool.

b. In Digital Marketing

    As we know Machine Learning allows a more relevant personalization and because of that companies can engage and interact with the customer in a customized way. By having information which can be leveraged to learn their customer’s behavior many companies using Machine Learning to write sales emails that are personalized ones that perform better.

    C. In Education

    Nowadays the education system is improvising itself. Even Teachers are using Machine Learning to keep on a check that how much of lessons students are able to learn, how they are coping with the lessons taught and much more. Of course, this enables the teachers to assist their students to grasp the lessons well. This all not only better the education domain but also prevent the at-risk students from falling behind.

So, we have seen the application & algorithms of Machine Learning which is somehow shaping the future and assures that the future is bright. 

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