How and Why should you learn ML to survive upcoming recession
Despite developments in technology and the hysteria that's going around, addressing some of the questions like are we moving towards recession is still very challenging.It is said, according to a new study of strong job growth, that the US economy could be at its peak unemployment. The fact that artificial intelligence has made it widely known to overblown over the impacts of automation on jobs. But the cloud of the next economic constraints is accumulating gradually. Many analysts believe this year's recession may reach a peak early, while others claim it may take a year or two. Anyway, learning ML is a good option walking into recession. Let us see why you should learn ML to survive the recession.
Companies using machine learning:Machine learning algorithms power Walmart product recommendations, that Uber ratings, fraud detection at top financial institutions, content displayed on social media feeds or on Google Maps via Twitter, it's just that machine learning career that is booming now because smart algorithms range from email to mobile apps to marketing campaigns that you use everywhere.Artificial intelligence, deep learning, ML be it anything. When you don't understand and know it, then within 3 years you'd be a fossil. So, in this article I mentioned reasons to learn machine learning online.
Better career opportunities
You are using ML apps, without understanding it. Already there is the future of machine learning. It's just that the machine learning profession is booming now because of smart algorithms from email to mobile apps to marketing campaigns you use everywhere. When you are looking for the most in-demand and exciting career domains, it is a smart decision now to get yourself educated with machine learning skills. Learning by machine is the bright star of the moment. Learning ML opens up a world of opportunities to learn machine learning applications in various vertical areas such as cyber protection, image recognition, medicine or face recognition for any industry that seeks to incorporate AI in its domain. With several machine learning companies on the verge of recruiting professional ML engineers, the brain behind business intelligence is becoming that.
Machine Learning Engineers receive good salary
The expense of a top, world-class specialist in machine learning can be compared to that of a top NFL quarterback perspective. The average machine learning engineer salary is $142,000.. An accomplished machine learning engineer can earn as much as $195, 752.
Machine Learning Engineer Salary by Country
UK £54,620
Canada $102,259
Australia $107231
India INR 874,691
Machine Learning Jobs on the rise
You need a special kind of person to create a hammer, but once you build it, you can give it to other people who use it to build a house." The big hiring is happening in all the top tech companies in search of those special kinds of people(ML engineers) who can build a hammer (machine learning algorithms). The work market for engineers in machine learning is not only hot but sizzling. A recent survey on the Indian job market found that in Bengaluru alone there are needs of 4000 machine learning engineers.
Lack of Machine Learning Skills
Digital transformation with the use of machine learning is the new victim of the ongoing skills gap to plague other parts of the software world. Any CIO looking to hire talent with machine learning expertise in New York taps into a talent pool of just 32 experts, of whom only 16 are potential candidates, according to Gartner's report. To continue with machine learning, every company faces many challenges and one of the top concerns for these organizations is staff shortage of machine learning skills.As of October 2017, a New York Time report estimates that there are less than 10,000 people in the world who have the necessary background and expertise for AI-related jobs like machine learning and deep learning. The demand for skilled learning engineers of machines far exceeds that modest amount.
Identifying these untapped machine learning opportunities does not require a PhD in math or statistics but a fast trip back to the fundamentals of math, algebra and statistics along with a solid machine learning MOOC is what's needed to get started in a successful machine learning career.
Machine learning link to Data Science
Machine learning seems like a shadow of data science. Machine learning career endows you with two caps, one for a position as a computer learner engineer and the other for a job as a data scientist. To become competent in both fields makes a person a hot commodity to most employers. This means you can analyze tons of data, extract meaning, and gain knowledge from it, and use that information later to train a model of machine learning to predict outcomes. A machine learning engineer also partners with a data scientist in many companies to better synchronize the work items. In addition, the Sexiest Job of the 21st Century has been voted data scientist so that one can start as a data scientist specializing in machine learning and become more desirable to employers.
I hope you have learnt reasons for learning Machine Learning. Let us see how to approach Machine learning as a topic to learn.
How to approach to learn Machine Learning
The days when ML awareness used to be an exclusive preserve for Ph.D. researchers and students are gone. Today, without having to enroll in a university, you can learn self taught ML. Although a formal education may be quite helpful. If you are not cut for higher grades, here are some useful tips for beginning with ML.ne Learning. Let us see how to approach Machine learning as a topic to learn.
Learn any Computer Language:
You need to get going with some programming knowledge under your belt. The best way to learn is Machine learning online course comes handy, because its possession of hundreds of data science libraries makes it easy in many machine learning projects. Learning and understanding is relatively easy too.
Get a high-end PC:
Chances are you'd only use tiny datasets when you start. But with the passage of time you may want to dive into more complex ventures. To get the most out of the learning experience, make sure your PC meets all criteria, like having a good enough Random Access Memory (RAM) and storage. You would also need high-quality Graphical Processing Units (GPUs) to play with Deep Learning (an ML algorithm).
Know the prerequisites:
Machine Learning derives much from three areas of mathematics: Statistics, Linear Algebra Calculus. If you're not at ease with Maths, don't worry. Many of the things that you really need to know are absolutely basic.
Read ML Academic Papers:
Several ML papers are regularly written, and reading lots of them is a good way to learn new things, and keep up with ML science.
Learn through videos:
There are many free videos on Youtube.
Read Forums and Join Online Communities:
Join online groups and forums that can help you track the learning process quickly.
Practice:
Practice makes man perfect. So, try your hands on machine learning projects and take part in Kaggle and related sites hosted contests.
Conclusion: