Can machine learning be self-taught?

There is barely any subject that you cannot learn yourself, and Machine Learning is no exception. You can master many skills in machine learning that will not only help you understand the subject better but also find out ways in which you can leverage it to solve real-world problems.

One of the best ways to go about it is getting enrolled in a machine learning online course. Why do I say this? Because just like you went to school to learn basic math, the alphabet, and scientific formulae, you need somewhere to start with. And what better than a course that isn’t expensive, allows you to learn at your own pace, and is taught by industry leaders?

But, before that, you need to brush up your knowledge in a few important subjects that you probably studied in your engineering or school days.


  • Calculus, Linear Algebra, and Probability


Since machine learning is quite dependent on statistical algorithms, you need to have a good hand in some of the advanced math subjects, such as calculus, linear algebra, and probability.

With the help of these, you will be able to use machine learning to cluster data, make predictions with it, and draw conclusions from it, just as a human would be able to.

Interestingly, if you feel this is a burden, you can always enroll in a good machine learning online course that is independent of your previous knowledge in such advanced math subjects. These are some of the best courses since they will only teach you the parts that are needed in machine learning, and therefore, speed up your overall learning process.

Also, with this, you will also be able to gauge whether your aptitude allows you to pursue a career in machine learning or not. Let’s not fool ourselves; there are many who are afraid of mathematics. So, if you feel calculus is too much for you, you can give it a halt and prevent yourself from wasting time engaging in something you probably won’t be able to grasp easily.


  • Programming and Coding


Even the people who have only heard of machine learning and do not know the slightest bit about what it’s like at least know that it requires basic knowledge of programming. You need to be able to apply the machine learning algorithms using a coding language. You will also need to modify datasets to make them work with the algorithms.

For this, one of the most advanced programming languages is Python. Not only is it a rather easier language to get a hold of, but it also exposes you to a hoard of in-built libraries, which make it much more seamless to apply machine learning algorithms.

Again, I would recommend that you take up an introductory machine learning online course that will also take you through the process of programming using Python. It isn’t all that difficult as it may sound!


  • Books and Videos


Pick up a book to learn what deep learning is.

Superficially speaking, deep learning is a subset of machine learning. Only when huge amounts of data and computational power are fed into the system will its algorithms be able to work properly.

Given the exponential increase in the usage of data, deep learning has recently gained immense popularity. You can go for a separate deep learning course by individual teachers or go through YouTube videos. Some of them are really good! (Jeremy Howard is one of them.)

Another good way to become well acquainted with deep learning is by reading books that specialize in teaching how to implement machine learning algorithms. If you’re more of a reader than a watcher, this is the best possible way you can learn deep learning.

If not, you can probably find a machine learning online course that also trains students in deep learning.


Once all this is done, you are set to apply machine learning algorithms to your very own datasets!

However, once again, I would recommend that you go for a paid online course in machine learning because they teach everything from scratch. In fact, they have faculty who have worked on real-world problems using machine learning algorithms. They can give you a hands-on learning experience. Moreover, there is no limit to when the course has to be finished. If you have other things in the pipeline, you can always take it slower or faster if you have nothing to do. Could it get any better than this?

Find a paid course that suits you, and get started!

Leave a Comment