Machine learning has gained a lot of popularity in recent years and you might be wondering whether or not it makes use of a lot of programming.
So, is programming required for machine learning? Machine learning makes use of a lot of programming in order to prepare the datasets and to run the machine learning algorithms. Two of the most popular programming languages used are Python and R.
Even though machine learning isn’t all about programming specifically, it does make use of a lot of programming. The programming languages used all have specific use cases and there are actually a lot of other skills that are required to make use of machine learning.
How programming is required for machine learning
Machine learning is where statistical algorithms are able to learn from large amounts of data and to make predictions based on that data. The machine learning algorithms do not need to be explicitly told how to make those predictions and they will adjust the predictions that they make when new data becomes available.
The algorithms that machine learning makes use of can require a lot of computational power and some of them need a lot of data to make accurate predictions. In recent years, computers have become a lot more powerful and businesses have been receiving a lot more data. This has caused machine learning to become a lot more applicable for businesses.
The reason that programming is used a lot in machine learning is that it is necessary to use programming languages to run these machine learning algorithms on the data.
You can watch the video below to see how you can make a simple machine learning program using a few lines of code:
What programming languages get used in machine learning
There are a number of different programming languages that get used in machine learning and each of them have advantages and disadvantages.
Python is the most popular programming language that gets used in machine learning. Python is mainly popular because it is one of the easier programming languages to learn, it has a large support community and it has a wide number of possible use cases. Additionally, Python comes with a large number of inbuilt libraries which allow for the machine learning algorithms to be run in only a few lines of code.
R is another popular programming language for machine learning especially for those in statistical fields. R comes with many builtin libraries that allow the machine learning algorithms to be used quickly. R is not as widely applicable as Python since its features are specifically designed for data analysis and statistics.
You can watch the video below to see more about popular machine learning programming languages.
How to learn programming for machine learning
There are many different ways that you can learn programming for machine learning.
My recommendation would be to learn Python if you are looking to learn it specifically for machine learning. There is a free and very highly rated course offered by MIT on EDX.org that will teach you how to code in Python from scratch. You can find the course here.
After you have taken that course or you have learned the basics of Python programming somewhere else then it will be necessary for you to learn some data analysis in Python. This is because it will be necessary for you to make the data useable by the machine learning algorithms. A good course on data analysis in Python would be this series on Youtube.
Other skills that you will need in order to learn machine learning
If you want to get into machine learning then there are a number of other skills that you will need to learn. To learn machine learning it will also be necessary to be proficient in calculus, linear algebra, probability and statistics.
There are a number of different ways that you can learn the above skills. Below, I will give you some links to courses that I would personally recommend.
Linear algebra (The University of Texas at Austin)
If you are looking for a job in machine learning then it is important to note that employers will typically be looking for candidates with at least a bachelors degree and more commonly a masters or even a Phd in a quantitative field.
How to get started in machine learning
If you are looking to learn machine learning then I would recommend that you start out by working through this course. It is a free course that does not require any prerequisite knowledge before starting the course. It will give you a very good overview of the different machine learning algorithms and how to make use of them.
After taking that course I would recommend that you learn how to program in Python and that you start making use of machine learning models on real datasets. To learn how to make use of machine learning in Python I would recommend this book which shows you how to make use of each of the different machine learning algorithms in Python. The book has prerequisite knowledge of calculus and linear algebra so it will be necessary for you to know those subjects first.
Once you have learned Python, calculus, linear algebra and probability then I would recommend that you take this course offered online by MIT. It will take you through each of the different machine learning algorithms in a slightly more mathematical way.
What are the prerequisites for machine learning?
You can start learning machine learning without any prerequisite knowledge by taking this course.
However, to make use of the machine learning algorithms in a more statistical and reliable way and to be able to fully understand them then it will be necessary to have a good understanding of calculus, linear algebra, probability and statistics. It will also be necessary for you to learn a programming language in order to implement the machine learning algorithms.
Does machine learning require coding?
In order to implement the machine learning algorithms it requires the use of computer programs so a lot of coding will be required. Coding will also be required because the data that machine learning algorithms make use of needs to be presented in a certain way that only can be done by making use of programming languages.