Machine Learning Applications Across Different Industries by@scarlett-rose

Machine Learning Applications Across Different Industries

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Machine Learning is being termed as a bridge which will help us leap into the future, transforming almost every single industry along the way. The benefits of Machine Learning outrank the downsides in so many ways that can save your business as well as help you gain more consumer trust. Up to 70% of contribution to web traffic comes from mobile devices, and up to 96% of active Facebook user accounts were accessed via smartphones and tablets. Machine Learning can help you develop strategies for improving your sales performance in both the short- and long-term.
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Scarlett Rose

Hey! I am a Software Consultant with 12 yrs exp. and blogging is my passion.

1952 witnessed the world’s first computer that could learn while it was running. It was a game of checkers developed by Arthur Samuel. It has barely been half a century since then and we’re already having a conversation about whether we should commercialize self-driving cars or not. Machine Learning gave birth to some of these great advancements in technology and we’re going to dive deep into everything it can do to make our lives much easier than ever before. 

What can Machine Learning do Today?

A lot of things, really. Machine Learning is being termed as a bridge which will help us leap into the future, transforming almost every single industry along the way. But before you get overwhelmed, let’s only focus on things that are currently popular among the business owners:-

= Analyze Sales Data


At present, business organizations can use analytical data so as to figure out the most valuable customers, i.e. the potential consumers that are most likely to convert into actual consumers. These companies know what consumes are browsing on social media platforms and other websites, and they target just the right ads to them. Not only can Machine Learning speed up the process of data collection, but can also analyze the data and present it to you in an understandable manner.

There are many tools for sales analytics that are available online, all of which are able to generate insights from sales data, trends, and metrics to set targets and forecast future sales performance. These Machine Learning tools will help you develop strategies for improving your sales performance in both the short- and long-term. You may read more about the sales metrics where you can find the right tools for getting started with the sales analytics.

= Real-Time Mobile Personalisation


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According to CIO Dive, up to 70% of contribution to web traffic comes from mobile devices. A recent web design stat suggests that 96% of active Facebook user accounts were accessed via smartphones and tablets. These numbers indicate a great degree of consumer inclination towards any form of mobile devices.

Mobile marketers and App Developers are looking for a way to leverage it so that they can develop a highly personalized mobile experience, which is where Machine Learning comes into play. Flybits is one company that helps other companies deliver real-time mobile app personalization. This allows you to have instant cloud access to internal and external data and enables you to develop personalized mobile channels.

= Detect Frauds


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Did you know that 2017 was a record year for the rise in e-commerce fraud? The data released by Experian suggests that e-commerce frauds in the US rose by 30% in 2017, compared to 2016. Considering that e-commerce sales only rose by 16%, it’s really unfortunate that these frauds rose by almost twice as much as the sales did, which is an alarming statistic.

Many e-commerce platforms like Amazon and Paypal have their own Machine Learning tools in order to prevent frauds ranging from abuse of promo codes to other payment-related frauds. You may read more about the kind of frauds that Machine Learning can protect you from. The benefits of Machine Learning outrank the downsides in so many ways that can save your business as well as help you gain more consumer trust.

= Personalized Recommendations


Who doesn’t like scrolling through the home page of an e-commerce website just to have a look at the product recommendations section for them? Well, nowadays, consumers even want to get notified on their smartphones about the latest offers available on their favourite product. Even if many of these consumers are indifferent, it skyrockets your chances of conversion since they’re being constantly reminded of their favourite products.

Amazon and Alibaba were one of the first e-commerce ventures to introduce an algorithm that improves the product recommendation process. John Bates, Senior Product Manager at Adobe, believes that by leveraging the power of Machine Learning and predictive analytics, brands can look beyond what consumers are looking for, and have them connect those dots for themselves about what they’re likely to want.

= Differential Pricing


Brace yourself, for the negotiation culture has finally reached the internet. I bet most of you didn’t know that the travel and retail industries are the masters of dynamic pricing, i.e. different prices for different consumers. This is another way for companies to make more money by changing the prices in accordance with the level of demand.

If you didn’t guess it already, there aren’t any humans sitting behind the scenes and changing these prices in real-time, it is Machine Learning that is changing the game for these industries. Both Uber and Airbnb use Machine Learning to create different prices for each person who is using their services. Uber also uses it for minimizing the waiting time and to optimize the ride-sharing aspect of its services. 

Applications of Machine Learning on Different Industries

Accenture, the tech giant, believes that current AI technology can boost your business’ productivity by up to 40%. Even Gartner, a popular Research and Advisory firm, predicts that by 2020, 85% of the customer interactions will be handled without a human. 

These machines have really profound algorithms that are designed to process a huge amount of information and to make decisions based on logic, enabling the machines to learn and to complete the task without any further programming. It goes without saying that Machine Learning has widened its spectrum and is taking over many industries. 

Let’s talk about some of these industries where Machine Learning has instantaneously grown popular:-

= Machine Learning Application in Transportation Industry


= Traffic Regulation
You know how much we all hate sitting in our vehicles, waiting for the lights to turn green, especially when there aren’t any vehicles coming in from the opposite side, but the traffic lights aren’t that smart, or are they? Well, Artificial Intelligence and Machine Learning algorithms seem to be taking over the streets of many countries and they’re efficiently able to predict, monitor, and manage the traffic. 

= Automated Driving
Just in case you didn’t get the memo, Self-Driving Cars are the future of transportation, and companies like Tesla and Google have already started doing their test runs. In fact, Tesla automobiles already have an autopilot mode that gives their cars semi-autonomous abilities. Once activated, the autopilot mode can regulate the car’s speed, change lanes, and park it without the driver’s assistance. 

Machine Learning Application in Healthcare Industry


= Diagnostics
The diagnostics running through Artificial Intelligence collects patient’s data to diagnose and suggest possible ways to prevent/cure the disease. Bear in mind that it’s only able to project a path with existing medication and not come up with new solutions. It just has the ability to detect medical problems much faster than a human can, which is pretty huge in itself when it comes to saving lives.

= Radiology and Radiotherapy
Dr. Ziad Obermeyer, an assistant professor at Harvard Medical School, did an interview with Stat News, where he made a bold claim saying that in 20 years, radiologists might look more like cyborgs, supervising algorithms while reading thousands of studies per minute. Don’t know how true that comes out to be but companies like DeepMind and UCLH are currently working on applying Machine Learning to help speed up the segmentation process and increase accuracy in radiotherapy planning.

Machine Learning Application in Finance Industry


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= Portfolio Management
If you’re a finance news reader or are into finance industry yourself, then you may have heard of Robo-Advisors. Robo-advisors is an online application that provides automated financial guidance. They provide portfolio management services that use Machine Learning algorithms and statistics to automatically establish and manage the investment portfolio of a client. It not only simplifies the investment process but is also cheaper than consulting a human financial advisor.

= High-Frequency Trading (HFT)
High-frequency trading, commonly termed as HFT, is a program trading platform that uses heavy duty computers to perform hundreds of thousands of trades at speeds way beyond human comprehension. According to Investopedia, during 2009-2010, about 60% to 70% of U.S. trading was attributed to HFT. It means that most investment banks, pension funds, and mutual funds, make use of HFT. It uses complex algorithms that analyze multiple markets and execute orders based on market conditions, which gives an edge to master investors as they are able to benefit from minute price differences that exist only for a fraction of a second.

Also Read: Tips to hire PHP developer for your business

Machine Learning Application in Agriculture Industry


= Crop Management
You know that these state-of-the-art approaches have come so far when we are able to predict crop yields based on historical data, and optimize productivity by multi-parametric approach, i.e. by analyzing the crops, weather conditions and even economic conditions to make the most of the yield. The same technology is being used to understand the crop quality, identify diseases and detect weeds.

= Field Conditions Management
Field conditions are important for the quality and quantity of the yield, which further facilitates the need for soil and water management. Machine Learning is able to study soil moisture and temperature to understand the dynamics of ecosystems and other hindrances in agriculture. Machine Learning based apps are also connected with daily, weekly and monthly estimates of evapotranspiration, enabling better use of irrigation systems.

Machine Learning Application in Education Industry


= Personalized Learning
Just like you have personalized recommendations on YouTube, the education industry is bringing about changes that will only show specific content to you based on your previous courses you took. We’re talking about the learning platforms that generally offer a systemized academic lessons like Udemy, Teachable, WizIQ, and many more. These are the platforms that are capitalizing on Machine Learning for the same, with the help of which the sellers, i.e. the online coaches, are able to target the right market.

= Increasing Efficiency
Have you ever heard of the saying, “When one door closes, another door opens”? Well, times have changed, and so have the problems. We have way too many doors open for us. The problem of the present day and age is to find the right door, on top of which comes a lot of scheduling and management of related routines. which is time consuming, and that’s exactly where Machine Learning comes into play. It makes educators more efficient by completing tasks such as classroom management and scheduling, meanwhile, humans can go focus on tasks these machines can’t perform. 

Additional Information

Is Machine Learning Different From Artificial Intelligence?

Before you read this article further, you must realize that Artificial Intelligence and Machine Learning are quite interrelated and both of these terms will often be used together, which means, whenever I talk about Machine Learning, Artificial Intelligence will most likely be a part of that conversation. Cool? Awesome. Let’s talk about how they seem to be different:-

Artificial Intelligence is a technology that makes machines capable of performing tasks in ways that are "intelligent." These machines are programmed to perform more than just a single, repetitive motion. In fact, they have the ability to adapt to different situations. 

Machine learning is technically a branch of Artificial Intelligence, but it's a lot more specific than the overall concept. Machine learning is based on the idea that we can build machines to process data, with the help of which they can learn on their own, without requiring constant supervision. 

Understanding with a Recent Example:-

Elon Musk’s company Neuralink has created a chip that people can get transplanted inside their heads, which will offer them the ability to not just think really fast, but to control computer devices with just their thoughts, and even interact with AI directly and way more efficiently. But the chip is so small that no human can possibly perform that operation. Keeping that in mind, they developed a neurosurgical robot that has a job to attach very precise threads into our brain. 

So, the Robot that’s performing the task autonomously is because of Machine Learning but its ability to learn more and adapt accordingly is because of Artificial Intelligence. 

Let's Wrap Up

There may be numerous applications of this technology, and surprisingly, it hasn’t even begun yet, but having made a leap that huge, that too, in such a short time span opens up so many possibilities in the present business models. No doubt, the rise of machine learning also brings the demand of mobile applications; therefore most of the businesses and agencies hire Android developers & hire iOS developers for integrating machine learning features in them.

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