Thousands of applications of Machine Learning are running around us. Some are hidden, some are obvious. Of course, we don't want to wake up one morning, surprised to be living cluelessly in a magical world operated by technology. In this article, we'll go through stories of how companies in Transportation, Financial Service and AdTech apply Machine Learning to provide the best services for all of us!
More and more people are familiar with transportation network companies like Uber and Grab. These Tech companies make our lives comfortable by providing vehicles to pick and drop us wherever we require. They have millions of customers, but few people actually know how Uber or Grab create such amazing services. Let's dig deeper into Uber.
We all know that Uber has gone out from Vietnam market a year ago, but Uber has still kept thriving worldwide in Canada, USA, Brazil, Singapore, and Japan. Uber has over 100 million worldwide users, and a 69% market share in the United States. After 10 years from its founding, now, Uber is valued at approximately 120 billion dollars. One of the reasons behind its success is the role that Machine Learning played in helping its business grow quickly.
How Uber solves supply and demand equations
Uber can predict upcoming demand of its customers by applying Machine Learning to process its historical data. These forecasts will notify Uber's drivers about where and when customers will be keen on finding cabs. This way, Uber makes sure that there are enough cabs in the right areas at the right times.
Uber's machine learning system updates the app with the conditions on every route and intelligently suggests and estimates the fastest route to the driver. The extensive amount of data they collect about car conditions allows these predictions to be very accurate.
Besides making the customers happy by decreasing wait time, drivers can serve more customers.
Money plays an indispensable role in our lives. We always try to use our money wisely and of course, prevent ourselves from debt. Debt can cause numerous troubles, not only for borrowers but also to lenders.
TrustingSocial doesn't use any traditional input values like frequency of when you pay your bill or how much of the bill is paid to calculate a credit score. This start-up leverages Machine Learning technologies and advanced data science to process the social, web and mobile data of each applicant. Therefore, it doesn't only give a credit score but also predicts the future of the borrower's credit worthiness.
Nowadays number of university students who are in debt is so common to make us generate a terminology for this "Student in Debt". TrustingSocial can help to warn the student of how much he or she has borrowed to push them to reduce their expenses. It also help businesses who lend money to more easily manage a whom they lend their money to.
Every business has to advertise. Knorex - a global adtech company providing precision performance marketing solutions, helps its clients to reach their target customers via multiple channels and all smart devices.
So how do they do it?
Automated Marketing Platform
XPO, Knorex's platform, takes digital advertising bid requests from media publishers worldwide through various advertising exchanges. Depending on demands of the clients, for each request, XPO will intelligently decide to proceed or not, and if so, at what price. Everything occurs automatically and quickly.
“For every bid request, we have to process and return the bidding decision in less than 100 milliseconds,” Phu Le, Head of R&D, Knorex said in an article with Google Cloud. "At any given time, hundreds of thousands of bid requests could be coming into the system, totaling billions per day."
While Knorex developed its own system leveraging Machine Learning, it also deploys a powerful tool - Google Cloud Machine Learning Engine to train thousands of independent machine learning models and the ability to automatically deploy and update them regularly when new data comes in.
This marketing strategy will soon replace all traditional methods because of their low degree of accuracy and time-consuming process.
Thank you for reading. If you are keen on learning Machine Learning, you should dig into these free materials in this article: Best Places to Teach Yourself Machine Learning for Free.
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