Why-You-Should-Not-Learn-Machine-Learning
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Machine Learning is one of the popular fields in tech right now. Many engineers and techies globally are trying to learn machine learning. You may think we are crazy to say why you should not learn machine learning?  Especially with tons of jobs available in the field of machine learning and to support the demand there are many online websites, forums, etc that can help you build your career in machine learning.

The truth is there has been a lot of hype created around machine learning. Machine learning certainly is a topic that will get many of us excited. It is claimed to offer solutions to all world problems.

Once the hype around machine learning dies and we may lose interest in it. Learning machine learning just believing it to be the next big thing. Don’t do it just because many companies are implementing it, it would be a wrong idea.

Statistics suggest machine learning has reached new heights. Many organizations across the world are leveraging machine learning to get ahead of the competition. The financial sector is one of the leading adopters of the technology to grow business using AI powers.

Statistics on Machine Learning AdoptionStatistics on Machine Learning AdoptionMany startups have cropped up with claims to integrate machine learning. Many use the term Machine Learning more as bait, to attract investors. Yet another reason for you not to learn machine learning.

Why Are So Many People Learning Machine Learning?

  • Many students have jumped on the bandwagon without any plan and will be the ones to give up easily. While the ones with proper planning will find it easy to understand. With so much information available you will be able to understand what to do with a skill set like a machine learning from the start.
  • Most of the beginner courses for Machine Learning cover a variety of topics such as image recognition, computer vision, time series forecasting, and so on. These are basically multiple topics that solve multiple problems. It consists of a number of topics and you need to know which one will solve your problems. It becomes important you know beforehand what kind of problem you want to solve with machine learning.
  • The third reason why you should not start learning machine learning is that you are not going to end up with a high-paying job. Though there are tons of hyped jobs available they come with many barriers. For example, Most of the jobs posted by Google will require you to have a Ph.D. This does not mean you require a Ph.D. to get a career in machine learning. Many engineers start off as data analysts or data scientists. The pay scale is not as high but is at par with a software developer.
  • Finally, it will get a lot easier for you to get a job now, but maybe over the next decade or so the number of jobs in machine learning will increase exponentially. There will be an increase in the demand for machine learning engineers to fill these roles. Yet the barrier of entry for these jobs will remain the same. There are not many opportunities available for entry-level roles in the last five years. Candidates require to have a minimum of five years of experience either as a data analyst, a data scientist or some sort of experience dealing with data in particular.

Please don’t think we are trying to discourage you from learning machine learning. We will keep bringing new information related to AI and Machine Learning to help you plan your goals and path in learning machine learning.