Machine learning: A Road to the Future

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application of ML

Twenty years ago, when we thought about the future, we fantasised about flying cars, teleportation and what not. Today, when we think twenty years ahead, what comes to your mind?

I think of holograms, more voice assisted devices and everything available at the touch of my hand. In other words, I think of Artificial Intelligence sitting on a throne and governing the world and the people in it. I imagine the current world moving towards its 4th industrial revolution in which disruptive technologies and trends such as the Internet of Things (IoT), robotics, virtual reality (VR) and artificial intelligence (AI) are changing the way we live and work.

 It is an era of accelerated technological progress characterized by new innovations whose rapid application and diffusion typically cause an abrupt change in society. Advances in automotive safety through Fourth Industrial Revolution technologies can reduce road fatalities and insurance costs, and carbon emissions. Autonomous vehicles can reshape the living spaces of cities, architecture, and roads themselves, and free up space for more social and human-centred spaces.

As we move towards the great technological revolution the world is about to witness, one can only imagine, how do I change myself to gain the most out of it?

The answer lies in two simple words i.e. Machine Learning.

Machine learning is an artificial intelligence course in bangalore that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers to learn automatically without human intervention or assistance and adjust actions accordingly.

The technology is infusing a deeper intelligence and understanding into the applications that touch our lives, to dramatically improve our experiences. In addition, it’s helping to spawn entirely new business innovations and models, such as autonomous vehicles and virtual personal assistants.

In fact, machine learning is so prevalent and pervasive that it’s difficult to imagine an enterprise being able to survive without embracing it in the next five years. Especially considering predictions of continued global data growth. This is why it is not only important, but critical to understand the current state of machine learning and what the future holds.

Here are the possible ways machine learning can be integrated in all of our personal lives in only a few more years and some are even present today!

  1. Virtual personal assistants

Today we have Siri, Alexa, Cortana etc. that tell us everything. They can put alarms, send texts, open applications and even tell us a joke when we are bored, all at just a voice-based command.

Machine learning is an important part of these personal assistants as they collect and refine the information on the basis of our previous involvement with them. Later, this set of data is utilized to render results that are tailored to our preferences.

  1. Face recognition services

This is one of the most prevalent technologies today and will seemingly be everywhere in the near future. Today, you upload a picture of you with a friend and Facebook instantly recognizes that friend. Facebook checks the poses and projections in the picture, notices the unique features, and then matches them with the people in your friend list. The entire process at the backend is complicated and takes care of the precision factor but seems to be a simple application of ML at the front end.

  1. Email spamming

There are a number of spam filtering approaches that email clients use. To ascertain that these spam filters are continuously updated, they are powered by machine learning. When rule-based spam filtering is done, it fails to track the latest tricks adopted by spammers. Multi-Layer Perceptron, C 4.5 Decision Tree Induction are some of the spam filtering techniques that are powered by ML.

  1. Product Recommendations

Yesterday I shopped for a wooden chair, today that e-marketing website sent me a product recommendation for a desk or a table that goes along with it. Now, I’m tempted to buy that table because it looks good with the chair I bought, boosting the company’s sales. Certainly, this refines my shopping experience but did you know that it’s machine learning doing the magic for you? On the basis of your behaviour with the website/app, past purchases, items liked or added to cart, brand preferences etc., the product recommendations are made.

There are so many other ways Machine Learning can be integrated in our everyday lives. It can impact everything from our morning alarms to banking applications.  Survival in the future will mean incorporating complex machine learning algorithms into business processes and having the ability to scale through new connections.

We may not have flying cars or teleportation yet, but we might just have a world that functions with the flick or our fingers with the help of machine learning.

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