Machine learning is the field of scientific study that equips computers with the power to understand and learn things without involving any explicit programming. It’s one of the most compelling technologies to have surfaced that make machines think and act similar to humans. Machine learning is a component of artificial intelligence that can be used to identify patterns from huge volumes of data and make data-driven decisions with the least human interference.
Presently, machine learning is finding active applications in several areas than one can imagine.
The Progression of Machine Learning
Machine learning came into being from the theory that computers, just like humans, can perform certain tasks without being programmed to do so. It enables computers to make sense of the data from previous computations or adapt themselves to new data and produce insightful and reliable results.
The science of machine learning is not a modern-day concept, but one that has gained momentum recently. Machine learning algorithms have been existing for quite a long time now. However, the ability to analyze complex data over and over is a recent development. The following machine learning applications show how the science of AI is changing the world for good.
Here are some examples of commonly found AI’s:
- Virtual assistants like Samsung Bixby and Apple’s Siri on smartphones.
- Displaying personalized feed on social media platforms based on the profiles you visit, friends you connect with, workplace, etc.
- Search engine result refining.
- Self-driving cars.
- Fraud detection, which is probably the most important purpose that machine learning could serve.
Why Should You Learn Machine Learning?
Now, machine learning has gone beyond the boundaries of the computer science field and is being widely used across several sectors. As the requirement of smart algorithms continues to emerge from email to mobile apps to marketing campaigns, a career in machine learning will become the most in-demand and most-exciting career domain. The future of machine learning is here, and gearing yourself with machine learning skills is a good move to make now.
1. There are better career opportunities in machine learning
Almost every industry is trying to tap into the possibilities that machine learning brings in like image and face recognition, cybersecurity, healthcare technology, etc. So, there is a great demand for skilled machine learning professionals.
Moreover, Netflix announced to offer $1 million as a prize to the person who could figure out a way of enhancing the accuracy of its recommendation ML algorithm by 10%. This clearly shows the significance that machine learning algorithms hold for industries in every vertical.
Machine learning has become the brain behind business intelligence, and if you wish to rank among the top software engineers, now is the best time to learn ML.
2. The pay for machine learning engineers is pretty good
The demand for machine learning engineers outpaces their supply. As mentioned earlier that companies are increasingly looking to adopt AI and ML in their technologies, ML experts can earn somewhere around $125,000 to $175,000. Sometimes, it can also go up to $200,000 to hire top talent candidates.
However, on average, the salary of a machine learning engineer is $142,000 as found by the statistics from SimplyHired.com.
3. There is an undersupply of machine learning skills in the market
As mentioned by a Gartner report on the availability of machine learning skills in New York, the CIOs found only 16 potential candidates who were ready to take on the job out of a talent pool of 32 experts.
Many organizations are already going through a tough challenge to begin with machine learning, and the shortage of engineers with expertise in machine learning is leading to a bigger problem.
According to a New York Times report in 2017, it was estimated that the number of people with the necessary skills and background for ML-related jobs is less than 10,000.
4. Machine learning has a direct association with Data Science
Machine learning seems to have a close linkage with data science. Going for a machine learning career gives you two great options – either you can choose a machine learning engineer job or take up a data scientist job.
If you’re competent in both the fields, you will be able to analyze tons of data, make sense of it, and develop a machine learning model to generate data-derived results. This will make you the most sought-after commodity for many companies. Many organizations also offer jobs to machine learning engineers to work in partnership with data scientists to achieve a better synchronization of work.
Therefore, someone starting as a skilled data scientist specializing in machine learning will definitely become a desirable professional to employers.
Who Can Opt for Machine Learning Courses?
As the machine learning field deals intensively with mathematics for the analysis of data and algorithms, you must have a mathematical or engineering background. Some of the mathematical concepts that you should have an idea of before going for a machine learning course are linear algebra, calculus, statistics, probability theory, calculus of variations, graph theory, and optimization methods.
If you’re looking to take up a career in machine learning, there are many courses available online. Here’s a link where you can find the best online courses for 2019.