How to start a career in Machine Learning?

Machine Learning

Ever since machine learning has successfully taken the leap out of the academic laboratories right into the heart of industries people have considered this as an alternative career path. Right now it is not even an alternative or unconventional career option, machine learning is main stream and lucrative. There has been a 344% increment in the average salary of a machine learning engineer from the previous year and there is still plenty of room for growth.

Before you start

You are probably well aware of this but it is sort of a liability on my part to introduce machine learning. Machine learning refers to the process of training a machine to perform a task without being specifically programmed to perform that task. You expose the machine to a vast amount of data and teach it to recognize certain details from that data. Then you provide it with some more data from which it brings out insight on the basis of the knowledge it had gathered earlier. It is definitely not as simple as it may sound when explained in laymen terms.

The initial approach

You have got to be very honest with yourself; know where you stand in terms of skill set and mark the tools that you need to learn from scratch as well as those in which you need some brushing up. For instance, a machine learning engineer may have to do a good deal of programming. The most preferred tool is Python. You might want to consider where you stand on Python programming. If you are confident about your Python skills, congratulations, one thing is off your list. You should not shy away from some training. Machine learning training courses are readily available in both off line and online mediums, just enrol for one.

Paid courses v/s free material v/s MOOCs

There is a lot of free material on various forums practically on any subject. In fact, there is enough to turn you into a machine learning professional without costing a dime (internet charges aside). What you need to realize is that it is not the material but the training and guidance that matters. As for the massive open online courses or the MOOCs, these can be really helpful if you already know a fair deal about a subject or in some cases if you get the basics from a MOOC and gain further knowledge from experts.

Compete and connect

Participating in machine learning competitions like the ones on Kaggle can really help you get going. Not only does this test your skills and get you excited to learn more but also help you connect with the peers. Building networks can never harm.

Consistent effort

For all I know, you could be a hard working employee trying to sneak into the world of machine learning. The key is in the weekends. Use your Saturdays to study and implement machine learning algorithms. Do this consistently and it will be only matter of time before you are good to go.

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