If you don’t know much about machine learning it may be tough for you to know how to start learning about it and what programming languages are best suited for it.
There are plenty of programming languages that can be used for machine learning but which one of them is the best for it?
This is what we will be talking about in this article, we hope that by the end of it, you will know everything about machine learning and which one of the programming languages is better suited for this field.
In the case that you know nothing about programming languages but are interested in machine learning. Our advice for you is to find online courses that can teach you the basics.
A good starting point would be the WantoDev website. They have great online programming courses for all levels and their beginner courses are a particular favorite of our staff.
What is Machine learning?
The term “machine learning” has been around since the 1950s, when researchers started trying to build computers that could learn things based on experience.
You can think of Machine Learning as a subset of Artificial Intelligence technology. It pretty much involves training a machine to learn more quickly.
You see, A.I. tech focuses on mimicking human intelligence but machine learning focuses on making that machine learn more and faster from experiences.
In a way, it is like optimizing the process of A.I.
The goal of machine learning is to make A.I. solutions faster and smarter so that they can deliver better results in whatever task they were assigned to.
Machine learning develops algorithms that can automatically extract patterns from large amounts of data. These algorithms can then be used to predict future outcomes based on past events.
Machine learning is now used in everything from self-driving cars to speech recognition software.
Uses for Machine Learning
There are numerous uses and applications for machine learning. We will talk about the ones that we feel are more common in our world and give you a quick explanation of what they do.
Speech recognition: If you have or use a speech recognition app or device, then you have seen machine learning in action.
These types of apps use machine learning to identify what you are saying and then translate that into text that the computer will understand.
Image recognition: Every time you do one of those wonderful CAPTCHAS or something that requires you to verify your identity by clicking some images, you are teaching the computer to understand the difference between the pictures.
Google also has a community app where people can help with verifying translations and also help the Google machine learning service to better recognize differences between various images.
Streaming services: This is one that you may use every day and probably don’t even know how it works. The more movies or series you watch, the more the machine learning algorithm will learn about what you like and don’t like.
Every time you watch your favorite shows, the system recognizes the activity and uses that to improve the recommendations of similar content you may enjoy watching.
Virtual Assistants: A.I. programs such as Siri, Bixby or the Google assistant learn about your habits every time you speak to your device.
Social Media and advertising: This one is probably the more well-known of the 5 we chose to talk about.
Social media platforms, and advertising in general, generate ads based on your likes and interests.
You must have noticed that if you search for something you want to buy online, all the ads become suggestions for that one thing you wanted to buy.
That is machine learning being used to give you better recommendations.
Other uses for Machine Learning
There are other uses for machine learning, we obviously can’t talk about all of them in detail but we can leave you more examples of them.
If you are curious as to how they work, you can do your own research, it is worth it!
- Self-driving autonomous cars
- Sentiment analysis
- Social media analysis
- Financial trading
- Fraud detection
- Product recommendation
- Medical diagnosis and predictions
Best programming languages for machine learning
As it was said at the beginning, there are a lot of programming languages that can be used in machine learning.
If you are considering having a career in this field, you are for sure wondering which one of the programming languages will be better suited for the job.
While there are many options to choose from, we decided to focus on the 4 programming languages that we feel are better suited for something like machine learning.
If you need to freshen up on the basics or even something more advanced, WantoDev has courses for the majority of languages we are going to talk about.
Python
When it comes to programming languages used by machine learning developers, Python is miles ahead of the competition. Python is used by over 60% of the machine learning developers.
There is a good reason for that. Python is easy to learn, scalable and open source.
Python comes with great visualization packages and useful libraries such as Pandas, Seaborn and Numpy.
As you can imagine, machine learning algorithms are very complicated, so having flexible and easily readable code can help the engineers to create the best solution possible for a problem they are working on.
If you need to learn more about Python, remember that WantoDev has a great online course that could help you improve your knowledge of this particular programming language.
R Programming
R is also a very popular programming language, but in this case, it is more popular for statistical computing, analysis, and visualizations in machine learning.
It is a graphics-based language used to explore statistical data via graphs. It is used by professionals from Facebook and Google for example.
It is a very powerful and useful language if you are dealing with a large volume of statistical data to process into readable data.
It helps engineers streamline large and complex data so that it becomes less overwhelming to analyze.
JavaScript/Java
Java is known as the jack of all trades when it comes to programming languages. It is not as dominant as Python but it is still widely used in the world of machine learning.
Java and Javascript are multipurpose languages that are known to be reliable and have the competency to support heavy data processing.
Most websites are actually created using these languages which makes the integration process of machine learning that much easier.
Remember Wanto.Dev? Well, they have online courses for beginners and for specialists in Java/JavaScript. Worth a look if you are looking to learn more about it.
C++ (C Plus Plus)
C++ is a programming language that is supported by most of the machine learning platforms we have used. If you have a good amount of knowledge of C++ then we feel that it is a pretty good idea to learn about machine learning with C++.
It is a superfast programming language that is popular among machine learning developers. When compared to other programming languages, C++ is just more efficient.
It also offers you powerful libraries such as the TensorFlow and Torch.
It is a great choice for performance-critical applications that need memory management and speed as priorities.
Choosing the best programming language for machine learning will come down to the nature of the job you have to do.
Each of the languages we spoke about are unique and are used for specific tasks.
Many machine learning engineers end up using multiple languages so testing and experimenting will be the best way for you to know which language you should choose.