Which programming language should developers learn in order to get work like machine learning or data science? This is a very important issue. We have discussed it in many forums. Now, I can provide my own answer and explain why, but let's look at some data first. After all, this is what machine learners and data scientists should do: look at the data, not the point of view.
Let's look at some data. I will use Trend Search on Indeed.com. It can search for specific terms in actual job opportunities based on time. This shows that employers are looking for talent with this skill. However, please note that this is not a poll of effective use of skills. This indicator is more representative of the popularity of skills.
Not much to say, on the data. I searched for the skills used with Machine Learning and Data Science. Search options include the programming languages ​​Java, C, C++, and JavaScript. Then included Python and R, because we know that it is very popular in machine learning and data science, and of course Scala, considering its relationship with Spark, plus Julia, some developers think this is "the next Big thing". Running, we get the following data:
Not much to say, on the data. I searched for the skills used with Machine Learning and Data Science. Search options include the programming languages ​​Java, C, C++, and JavaScript. Then included Python and R, because we know that it is very popular in machine learning and data science, and of course Scala, considering its relationship with Spark, plus Julia, some developers think this is "the next Big thing". Running this query, we get the following data:
When we focused on machine learning, we got similar data:
What inspiration can we get from these data?
First of all, we see that it is not a single pass. In this case, various machine learning programming languages ​​are very popular.
Second, all of these programming languages ​​are growing dramatically, reflecting the increasing interest and demand for machine learning and data science in the past few years.
Third, Python is a clear leader, followed by Java, then R, then C++. Python's lead over Java is increasing, and Java's leading position on R is declining. I must admit that I was surprised to see that Java is ranked second; I originally thought it was the R language.
Fourth, the growth of Scala is impressive. It almost did not exist three years ago and is now on the same level as these mature programming languages. This is easier to find when we switch to the relative view of the data on Indeed.com.
Fifth, although Julia's popularity is not obvious, there is definitely an upward trend. Will Julia become a popular machine learning and data science programming language? I will tell you in the future.
If we ignore Scala and Julia so that we can focus on the growth of other programming languages, then we can no doubt confirm that Python and R are growing faster than the common language.
Given the difference in growth rates, R's popularity may soon outweigh that of Java.
When we focus on the problem of deep learning, the data is completely different:
At this time, Python is still the leader, but C++ is now the second, then Java, and C is fourth, and R is only fifth. The high performance computing language is clearly emphasized here. Java is growing rapidly. It can reach the second place very quickly, just like general machine learning. R won't get close to the top soon. To my surprise, Lua was absent, although it was used in a major deep learning framework (orch), and Julia did not exist.
At this point, which language is the most popular programming language? The answer should be clear. Python, Java, and R are the most popular skills when it comes to machine learning and data science. If you want to focus on deep learning instead of general machine learning, then C++ and C are worth considering to some extent. However, keep in mind that this is just one way of looking at the problem. If you are looking for a job, or if you just want to study machine learning and data science in your spare time, you may get different answers.
What is my personal answer? In addition to the support of many top machine learning frameworks, Python is a good fit for me because I have a background in computer science. I also feel comfortable developing new algorithms, because most of my career has been programmed in this language. But this is me, people with different backgrounds may feel better in another language. A statistician with limited programming skills will definitely prefer R. A powerful Java developer can use his favorite language because there are plenty of open source Java APIs. A similar example can be found for any of the languages ​​on these charts.
Therefore, my suggestion is to decide which programming language to choose based on your own situation before spending a lot of time learning a language. Remember to never follow suit.
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