Is Machine Learning Worth Learning?

When I first started learning machine learning I wondered whether or not it was worth learning.

In this post, I hope to help you decide whether or not learning machine learning would be worth it for you.

So, is machine learning worth it? Machine learning careers offer high salaries, it’s currently an in-demand field and there are many interesting use cases of machine learning. If you enjoy math, programming and statistics then learning machine learning would likely be worth it for you.

There are actually a number of considerations to make when deciding on whether or not to learn machine learning. Depending on your background, there could also be a lot that you will need to learn before you can fully make use of machine learning.

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Is it worth it to learn machine learning?

Below, I will mention the advantages and disadvantages that machine learning has and other things that you should consider when deciding on whether or not to learn machine learning.

What you can do with machine learning

Machine learning is all about analyzing large amounts of data and using that data to make predictions.

Machine learning gets used in many different fields and it has many different uses cases. Here are a number of things that machine learning can be used for:

  • Financial trading (predicting the future prices of stocks)
  • Healthcare (detecting diseases, improving health records, predicting outbreaks, etc)
  • Education (optimizing lessons based on student retention, digitizing formulas from photos, etc)
  • Marketing (predicting consumer behavior)
  • Building recommendation systems (ie: recommending shows on Netflix or products on Amazon)
  • Natural language processing (making sense of human language)
  • Self-driving cars

How well machine learning pays

According to GlassDoor the national average salary for a machine learning engineer is $114,826.

The actual pay that you would be able to get would greatly depend on the location, your experience and educational background.

Entry level positions will typically require a masters degree. However, if you have a bachelors degree and you can show relevant work experience then you will still have a good chance of being able to get an entry-level position. You can show relevant work experience in the form of internships and/or projects. According to PayScale, the 10th percentile of machine learning engineers earn $74,000 per year.

On the other hand, the more advanced positions that will typically require either a phd or a masters degree and relevant experience. According to PayScale, the 90th percentile of machine learning engineers earn $143.000.

The location that you work in will also have a big impact on the salary that you can earn. Salaries in the Bay area will typically be much higher than those everywhere else but the cost of living is very high as well.

How in demand machine learning is

In recent years, there has been a data explosion resulting in many big (and small) companies trying to find ways to make sense of, and to make use of, that data. As a result of this, people with knowledge in machine learning have become highly sought after.

According to Indeed, the demand for AI-related roles has more than doubled over the past three years but the supply has plateaued. This means that, if you can gain the required skills, and you can show that you have them then it shouldn’t be too hard for you to find a job in machine learning.

As mentioned above, machine learning has a wide range of possible use cases in a variety of different industries ranging including education, healthcare, business and finance. As a result of this, you should also be able to find ML work in a field that interests you.

There are many machine learning based startups

If you are interested in making your own tech startup then machine learning and AI are fields that you should take a close look at. This is because we are currently experiencing a boom in AI-related startups as people are just beginning to find new and interesting ways to make use of the data that is available to us.

You can watch the video below to see how you might go about making an AI startup of your own.

Of course, if you are not interested in taking the risk of making your own tech startup then you do also have the option to work for these startups instead (just don’t accept pay in the form of stock options).

What you will need to learn

The amount that you will need to learn will depend largely on what you intend to do with machine learning.

However, if you want to be able to fully understand how to make use of machine learning and how the machine learning algorithms work then there will be quite a lot to learn. To understand machine learning it will be necessary to have a good understanding of calculus, linear algebra, probability, statistics, programming and data analytics.

If you’re looking to get a job in ML or to be a data scientist then it would be more beneficial to have a good knowledge of python and data analytics. If you’re looking to be an ML researcher then it will be necessary for you to have a good understanding of the R programming language.

If you’re looking to self-teach yourself any of the subjects above then I would highly recommend checking out the free courses offered on the edx platform. On the platform, you can find courses offered by top universities in ML and in many ML related topics.

It’s a rapidly changing field

Machine learning is a fast-changing field and if you want to go far in machine learning or AI then it will be necessary for you to keep up with the latest developments.

If you enjoy learning new, challenging, things then machine learning would likely be an interesting subject for you to learn. Whereas, If you would prefer something that is more established then the field of machine learning might not be the best option for you.

Consider what your goals are

When considering whether or not it would be worth it for you to learn machine learning it would help to consider what your goals are.

If you are looking to learn machine learning to get a job then the good news for you is that it was voted the best job of 2019 by Indeed. This was largely due to its high salary and it’s 344% growth in job postings between 2015-2018. However, it is important for you to be aware that it will normally be necessary for you to have at a minimum a bachelors degree and more commonly a masters degree.

If you are looking to challenge yourself in an interesting way then learning machine learning would also be worthwhile for you. It is a field that has many interesting use cases and is rapidly developing.

However, if you do not already have the skills and you need to get a job quickly then you might want to hold off on machine learning for now. This is because, depending on your background, it will likely take you a while to learn all of the required skills especially if you don’t have a strong background in math or programming.

Consider what your interests are in

It would also help to consider what you are interested in.

If you have a strong interest in mathematics, statistics and programming then machine learning would likely be a good field for you to enter since it makes use of all of them.

However, if you don’t enjoy math that much as many people, unfortunately, do not then ML probably wouldn’t be a good fit for you and you might want to consider something like software engineering instead.

With that being said, in order to get the machine learning algorithms to work with your data, it will be necessary for you to clean and to preprocess the data. Depending on the dataset that you are using, it can be time-consuming and, at times frustrating, to do this.

If you want to go far in machine learning it will be necessary for you to spend a lot of time preparing data. If you don’t enjoy dealing with poorly organized data then you might not enjoy machine learning that much.

If you are interested in learning machine learning then I would recommend that you start out by either looking at the free Andrew Ng course on Coursera or the book Hands on Machine Learning by Aurelien Geron.