4 misconceptions in machine learning | ML relality

4 misconceptions in machine learning | ML reality: Machine learning is a really popular field in tech right now and a lot of people are trying to learn it. Every second person these days is trying to get a job in machine learning. In fact, daily people search on the internet about how to they can learn machine learning and how they can build careers in machine learning. Machine learning is a field with a lot of potentials and you should definitely get into it. But today I will be telling you who should not get into this field become of

Machine learning is not easy, so before making a choice of your future job you should think critically. So let’s start.

Simple fell to learn.

One reason why not learn machine learning is if you’ve simply fallen to learn it. Study shows that machine learning has hype around it. So people have sort of FOMO over machine learning. It has an incredible amount of hype around it and in fact, so many experts have claimed that ML is the future for all solutions. But it’s not true.

Soon it will die down and the hype will be gone. And slowly you might actually lose interest in it. So ask yourselves, do you have a real interest in machine learning, do you believe this is going to be the next big thing. A lot of companies are doing this and in fact, so many startups have popped up just over a couple of years. Claiming to have machine learning solutions in their products. But many of these startups failed.

Don’t get into machine learning if you don’t have a plan

If you don’t have a plan don’t get into it. I mean to say that actually many students who have started learning machine learning simply did not have a plan and that has caused them to give up. While learning anything with a plan it’s way easier than students who have no plan. Since the learning curve for something like machine learning is really great. So if you have a plan from the very beginning it’s going to make things a lot easier and clear. Because there’s so much information out.

Without a plan, you will unnecessarily waste your time jumping between different courses. And end up learning very little. The thing with a lot of beginning machine learning courses is that they cover a lot of different aspects of machine learning like

  • image recognition
  • computer vision
  • time-series forecasting

So all these different things can actually solve very different problems. So it helps to know what kind of problem you’re intending to solve. This will save a lot of time and effort. And you can focus and give time in learning specific things.

Don’t think you will get a high salary.

Is simply because you believe that you know it’s going to give you a high-paying job, Not to get me wrong there are tons of jobs in machine learning. It’s simply that these high-paying jobs have a really high barrier of entry. If you are looking for a company like Google most of its machine learning jobs require you to have a Ph.D., to begin with. So think about all the time and effort it goes into getting a Ph.D. Also, think about all the money that goes and the financial investment in getting PhD.

Now that doesn’t mean that you need to get a Ph.D. to start a career in ML, not at all. A lot of machine learning engineers start off as data analysts or data scientists. Their pay is not high but it’s definitely along the lines of software developers.

The reality of machine learning jobs.

Over the next decade. The number of jobs in machine learning is going to increase exponentially along with a deal of demand for ML engineers. But one thing for sure that the barrier of entry for these jobs is not going to decrease by any means. It’s still going to remain pretty high. A lot of the machine learning jobs which have come out are not for entry-level roles. In fact, they ask for a minimum of five years of experience.

Conclusion:

4 misconceptions in machine learning are not to discourage you guys from learning machine learning. This blog was only written to make your goals and your path in learning machine learning clear. I think the biggest takeaway from this is that

  • having an end goal in mind.
  • also, be aware of exactly the kind of problem that you would want to solve with machine learning

Must read: 5 best and free Machine learning online course – Hot MIT course

Machine Learning Training | Learn Machine Learning Online | Internshala Training

I hope you enjoyed this and I hope it was really helpful for you guys. If you have any questions leave them down in the comment box below. Share and comment.

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