5 Ways Machine Learning Impacts Your Everyday Life

Machine learning is a concept that has gained immense popularity in the past few years and continues to do so as the field of Data Science makes rapid strides. ML is described as a subfield of Artificial Intelligence (AI) in which the system is provided with the ability to automatically learn from data and improve from experience without being directly programmed to do so.  

 

Speaking of Artificial Intelligence, you can also sneak a peek at some of our other blogs on this topic. 

 

Basically, Machine Learning involves training computers on available data using an algorithm(s) to create a model and then, this model is applied to the previously unseen data to make predictions.

 

Many of you might not be aware but ML is quietly making a significant impact on our day-to-day life, thus making our everyday living hassle-free. 

 

Here are the 5 ways through which ML has penetrated everyday life.

 

1. Spam Email Detection

 

Having an email id is no big deal nowadays. Whenever we login to our email id, there is a folder available in the sidebar named ‘spam’ that contains all the unwanted emails. And all those emails in the spam folder aren’t shifted manually from the inbox by the user. This is done automatically with the help of ML.

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Email classification using spam classifier

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A variety of algorithms – the most popular ones being Naive Bayes, K-Nearest Neighbours, and Random Forest are used for spam-filtering. These algorithms use the mails that have been previously successfully pre-classified as spam or non-spam as the training set.

 

Then, they are trained on this dataset and the consequent model created is applied to the new set of received emails for classification into spam or non-spam. Very simple yet effective use of ML capabilities. Out of many abilities of machine learning detecting fraud emails is one of the simplest yet effective ways.

 

2. Search Engines

 

Whenever we are looking for an answer to our queries, the first resort for most of us is to turn to search engines like Google, Yahoo, Bing, etc. and we type our query, press enter and we are provided with a plethora of links that are relevant to our intended query. But how do these search engines come to know what we are looking for? Again, the power of ML is getting harnessed for this purpose. 

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Using algorithms like Natural Language Processing (NLP), Deep Learning, and Tensorflow, search engines can decipher the meaning of search query and makes sure that the most relevant results of the highest quality are shown at the top. RankBrain is Google's machine learning model for predictive searches, it uses machine learning to find a connection between searchers and users.

 

3. Transportation

 

Most of us are very well-versed with traveling via cabs that can be booked through mobile apps such as Uber, Ola, etc. All these apps harness the power of ML. When you book a cab, the ML algorithms in place to make sure that the driver is nearby your location or the one going to travel on the same route as your destination (when pooling) picks you up.

 

And not just this, ML is also utilized to provide the fastest route to your destination based on a traffic jam, ongoing construction work, or any other possible obstructions occurring on the way to your destination.

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Traffic management system using ML

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1. With the help of image detection techniques, machine learning has already shown its potential in an automated or self-driving car.

2. It can take care of engine safety by collecting data and predicting the health of the engine. Also, it can manage the passenger’s safety

3. Traffic sign detection for better traffic management.

 

4. Online Recommendation Engines

 

Thanks to the advent of the internet and the rapid advancements that have been made in this field ever since we have got a variety of sources of entertainment to access. While the likes of YouTube, Netflix, Amazon Prime are the ones to-go-to when it comes to watching online streaming of movies and TV series, audio streaming apps such as Spotify provide quality real-time access to your favorite music.

 

And the fun isn’t just restricted to entertainment as multiple platforms are out there that allows you to do a variety of activities like purchase groceries, order food, buy stuff for your home, etc from anywhere in the World. 

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ML influence in online recommendations

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The one common thing among them all is the recommendation engines that provide the user with suggestions such as ‘similar products’ or ‘people who bought this also this’ when you select/purchase a product. All these oh-so-perfect recommendations are being made possible thanks to, once again, ML.

 

All the companies providing such online services store the data provided by the user (past searches, purchases, etc), and based on these, they make recommendations based on your behavior and preferences. 

 

5. Fraud Transaction Detection

 

There are millions of transactions being made every day online. Of them, there is always a chance of some of those being fraudulent. It won't be possible for the employees to manually go through each transaction and find the ones that seem suspicious. Not only it would cause the customers potential huge financial losses, but it would also lead to massive loss of potential revenues for the banks as well as customers would begin to drift away from them.

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Fraud Detection using ML

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