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Machine Learning is an application of Artificial Intelligence. It
allows software applications to become accurate in predicting outcomes.
focuses on the development of computer programs, and the primary aim is
to allow computers to learn automatically without human intervention.
Google says “Machine Learning is the future,” and the future of
Machine Learning is going to be very bright. As humans become more
addicted to machines, we’re witnesses to a new revolution that’s taking
over the world, and that is going to be the future of Machine Learning.
More online businesses are integrating machine learning into their
operations, with the bigger and established ones trailblazing the
revolution.
Machine learning has brought myriad opportunities and improved
strategies to help business owners foster customer relationships and get
more profit and conversions.
If you haven’t fully leveraged the power of machine learning in your
business, let me give you five reasons why you should do so now.
Amazon, for one, has applied machine learning to make grocery
shopping ultra-efficient for your customers through computer vision,
sensor fusion, and deep learning algorithms.
Using the Amazon Go app, customers only need to open it, scan the QR
code when they enter, pick their items, and confidently walk out of the
store.
Amazon Go detects the items they take out from the shelves,
automatically adds them into their virtual carts, and charges the bill
into their Amazon accounts when they leave.
Such is a classic example of how machine learning can increase the
efficiency of your business operations and processes, and help your
customers, too.
The concept may sound complicated, but through the right machine
learning course, you can invest in building machine learning
technologies that suit your specific business needs.
Machine learning can analyze and organize patterns, trends, and data
about your customers’ demographic profiles, choices and preferences,
behaviors, and others.
For instance, for your advertising campaigns on Google Adsense or
other channels to be effective, they should be deeply targeted according
to the mentioned data.
When customers feel that your offers are accurately aligned with
their preferences — or personalized — they are more likely to patronize
your business.
Flybits is a context-as-a-service product that helps businesses
provide hyper-personalized digital content and experiences for your
customers.
With its easy user interface, your digital marketers can easily and
instantly access internal and external data through cloud
synchronization.
Its real-time mobile analytics allow you to customize your content
and campaigns for your customers according to their location, weather,
and others.
What’s more, Flybits ensures your customers’ data are safe and kept
confidential. Your customers retain full ownership over their data as
well.
In line with personalizing your campaigns, machine learning can
recommend products similar to what you previously viewed, purchased, or
added to your cart.
Machine learning picks up on the features of the items you previously
searched, viewed, or bought, and creates algorithms from those data.
Machine learning notes the features of the shoes, such as color,
size, and style, and then shows you what other customers also bought.
In this way, they leverage social proof and fear of missing out
(FOMO) to entice you to consider buying what other customers also liked
(besides widening your range of options).
The convenience that online payment systems offer, especially through
mobile applications, has attracted both customers and businesses to
transact and purchase online.
If you’re experiencing the same problem, there’s fortunate news for
you. Machine learning can now help strengthen businesses’ fraud
detection system.
For instance, PayPal uses machine-learning mechanisms to catch
suspicious and shady transactions and separate them from legitimate
ones.
Machine learning further assists you by inspecting specific
attributes among your data and develop standards as the basis for
examining each transaction.
According to a Tractica Report, AI driven services were worth
$1.9 billion in 2016 and are anticipated to rise to $2.7 billion by end
of 2017 of which 23% of the revenue comes through machine learning
technology.
A report from TMR mentions that MLaaS (Machine learning as a
Service) is expected to grow from $1.07 billion in 2016 to $19.9 billion
by end of 2025.
Machine learning is the shining star of the moment. With every
industry looking to apply AI in their domain, studying machine learning
opens world of opportunities to develop cutting edge machine learning
applications in various verticals – such as cyber security, image
recognition, medicine, or face recognition. With several machine
learning companies on the verge of hiring skilled ML engineers, it is
becoming the brain behind business intelligence. Netflix announced prize
worth $1 million to the first individual who could enhance the accuracy
of its recommendation ML algorithm by 10%. This is a clear evidence on
how significant even a slight enhancement is in the accuracy of
recommendation machine learning algorithms to improve the profitability
of Netflix. Every customer- centric organization is looking to adopt
machine learning technology and is the next big thing paving
opportunities for IT professionals. Machine learning algorithms have
become the darlings of business and consumers so if you want to put
yourselves somewhere in the upper echelon of software engineers then
this is the best time to learn ML.
The cost of a top, world-class machine learning expert can be related
to that of a top NFL quarterback prospect. According to
SimplyHired.com, the average machine learning engineer salary is
$142,000.An experienced machine learning engineer can earn up to $195,
752.
“You need a special kind of person to build a
hammer, but once you build it, you can give it to many people who will
use it to build a house.”
The major hiring is happening in all top tech companies in search of
those special kind of people (machine learning engineers) who can build a
hammer (machine learning algorithms). The job market for machine
learning engineers is not just hot but it’s sizzling.
According to the popular job portal Indeed, the number of open
machine learning jobs have been steadily rising from 2014 to the onset
of 2016, from 60 job postings per million to more than 100. The number
of job postings jumped up to 150 postings per million by end of 2016.
Indeed job trends report also reveals that the number of machine
learning engineer job postings outstrip the number of searches for
machine learning jobs – 100 million searches vs. 150 job postings.
A recent survey on the Indian job market found that there is a
requirements of 4000 machine learning engineers in Bengaluru alone.
Machine learning appears as a shadow of data science. Machine
learning career endows you with two hats, one is for a machine learning
engineer job and the other is for a data scientist job. Becoming
competent in both the fields makes an individual a hot commodity to most
of the employers. It means that you can analyse tons of data, extract
value and glean insight from it, and later make use of that information
to train a machine learning model to predict results. In many
organizations, a machine learning engineer often partners with a data
scientist for better synchronization of work products. Furthermore, data
scientist has been voted the Sexiest Job of 21st Century so one can get started as a data scientist specializing in Machine Learning and become more desirable to employers.
Are you ready to learn machine learning and land your dream job at
one of the top tech companies? Share your personal approach, knowledge,
and strategy in the comments below. Everyone has a different take on
machine learning, and we want to know your thoughts.
can be a competitive advantage to any company be it a top MNC or a
startup as things that are currently being done manually will be done
tomorrow by machines. Machine Learning revolution will stay with us for
long and so will be the future of Machine Learning.
We have studied the future and the algorithms of Machine Learning.
Along with that, we have studied its application, which will help you
deal with real life. Furthermore, if you have any queries, feel free to
ask in the comments section.