Why you should learn machine learning?

Find out the top reasons to learn machine learning by understanding the scope and job opportunities for pursuing career as a machine learning engineer.

Why you should learn machine learning?
 |  BY ProjectPro

“Machine Learning is the new SQL for Big Data “

This quote illustrates that machine learning will be a major bifurcation in 2018.

Machine Learning is no longer just a niche subfield of computer science but technology giants have been using it for years – Machine learning algorithms power Walmart product recommendations, surge pricing at Uber, fraud detection at top financial institutions, content that Twitter, LinkedIn, Facebook and Instagram display on social media feeds or Google Maps. Machine learning products are being used daily, perhaps without realizing it. The future of machine learning is already here, it’s just that machine learning career is exploding now because of smart algorithms being used everywhere from email to mobile apps to marketing campaigns. If you are in search of the most in-demand and most-exciting career domains, gearing up yourself with machine learning skills is a good move now.


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Why you should embark on a machine learning career?

Learning Machine Learning Online

Artificial Intelligence, deep learning, machine learning — whatever you’re doing if you don’t understand it — learn it. Because otherwise you’re going to be a dinosaur within 3 years.”- said Mark Cuban, a serial entrepreneur.

Evolution of Machine Learning Applications in Finance : From Theory to Practice

1) Learning machine learning brings in better career opportunities

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.

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2) Machine Learning Engineers earn a pretty penny

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.

Average Machine Learning Engineer Salary

Machine Learning Engineer Salary

Country

Average Machine Learning Engineer Salary

USA

$134,283 

UK

£54,620 

Canada

$102,259 

 

Australia

$107231

India

INR 874,691 

 

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3)  Machine Learning Jobs on the rise

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.

Here is a snapshot of the total number of machine learning jobs in US for IT professionals as of November 13, 2017 –

Machine Learning Engineer Jobs Positions on Glassdoor.com – 12000+

Machine Learning Engineer Jobs

Machine Learning Jobs on Dice.com – 8000+

Machine Learning  Job Listings on Dice

 

Machine Learning Jobs on Indeed.com   - 6500+

Open Machine Learning Jobs on Indeed.com

 

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4) CIO’s Lament Lack of Machine Learning Skills

The new victim to the continuing skills gap to plague many sections of the software world is digital transformation with the use of machine learning. According to Gartner report, any CIO looking to hire talent with machine learning skills in New York taps into a talent pool of merely 32 experts, of which only 16 are potential candidates. Any organization faces several challenges to begin with machine learning and one of the top concerns for these companies is shortage of personnel with machine learning skills.

A New York Time report as of October 2017 estimates that there are less than 10,000 people in the world that have the required background and skills necessary for AI related jobs (Machine learning and Deep Learning). The demand for skilled machine learning engineers far exceeds that modest number. Spotting these untapped machine learning opportunities does not require a PhD in Math or Statistics but a brief trip back to basics of Math, Algebra and Statistics along with a comprehensive machine learning MOOC is what required to get started for a successful machine learning career.

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5) Machine learning is linked directly to Data Science

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.

If these reasons ring a bell then you might be interested to get your start in machine learning career right now.

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.

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ProjectPro

ProjectPro is the only online platform designed to help professionals gain practical, hands-on experience in big data, data engineering, data science, and machine learning related technologies. Having over 270+ reusable project templates in data science and big data with step-by-step walkthroughs,

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