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8 Machine Learning Language Rankings-Python and Libraries !


In recent years, the use of AI has spread, and many people may have heard terms such as Python, but do not know what machine learning and language actually are.

Here, we will explain various things about machine learning and languages ​​in an easy-to-understand manner, such as the relationship between machine learning and programming languages, what languages ​​are recommended, and how to learn languages. .

Table of Contents

  • Machine learning review
    • What is machine learning
  • What you can do by learning a language
  • The relationship between machine learning and deep learning
  • How to choose a programming language that can develop machine learning
    • Is there a demand for language
    • Easy to learn
    • Is the development community and teaching materials abundant?
    • How many libraries are supported?
  • Language ranking used for machine learning
    • 1.Python
    • 2.R.
    • 3.Julia
    • 4. JavaScript
    • 5.C++
    • 6.Java
    • 7. Haskell
    • 8. Matlab
    • Comparison table
  • What is Python that is often used for machine learning development?
  • machine learning language library
  • [Must-see for beginners] How to learn a programming language by yourself
    • Basic learning
    • Applied learning
  • Summary

Machine learning review

First, let’s review machine learning. A solid understanding of machine learning will help you understand how it relates to language.

What is machine learning

Machine learning, also called ML (Machine Learning), is a computer algorithm that automatically improves by learning from experience. Simply put, AI is designed to learn data and perform complex and difficult processing such as data classification and prediction on behalf of humans.

Without machine learning, AI cannot autonomously perform the above-mentioned processes. Therefore, it can be said that machine learning is an important technology that supports AI.

What you can do by learning a language

So how are machine learning and language related?

Learning a language allows us to program AI, and programming enables machine learning.

Machine learning programming is an essential process in creating AI, and it is necessary to be able to master the language for programming.

The relationship between machine learning and deep learning

Deep learning is a technique developed from machine learning and is a type of machine learning.

Deep learning is based on a technology called a neural network, which mimics the structure of human nerve cells (neurons). By using a neural network, it becomes possible to derive the correct answer by going through a process that is very similar to the human recognition process, enabling higher-performance learning.

How to choose a programming language that can develop machine learning

As I introduced earlier, machine learning requires language programming.

However, many people do not know which programming language to learn. Here, we will divide the selection method into four points.

  1. Is there a demand for language
  2. Easy to learn
  3. Is the development community and teaching materials abundant?
  4. How many libraries are supported?

I will explain each.

Is there a demand for language

The first thing to consider is whether the language is in demand.

If the language is too minor, there is a possibility that it will not be possible to lead to project orders, so it is necessary to choose carefully. Let’s start learning after thoroughly investigating whether the language has many projects related to artificial intelligence development.

Easy to learn

The second point is the ease of learning difficulty.

Each language has its own ease of learning. Trying to learn a language is pointless if you can’t master it.

Learning programming and mathematics at the same time is time-consuming, expensive, and unreasonable. If you don’t feel confident, start with a language that has simple grammar and is suitable for beginners.

Is the development community and teaching materials abundant?

The third point is whether the development community and teaching materials are abundant.

Some languages ​​have few participants in the domestic development community and few study sessions are held. Also, in such a minor language, it would be difficult to find blog articles or posts summarizing error-solving methods that can be used as a reference during development.

Therefore, it is recommended to choose a major programming language as the main programming language for smooth development.

How many libraries are supported?

The fourth point is the number of supported libraries.

First of all, a ” library ” is programming that allows anyone to easily use a series of highly versatile processes. The library is provided as an independent component, so that when you want to perform a specific process, you can load and use as many as you need.

The more libraries you have, the more efficient your programming will be, and you will be able to create whatever you want.

Also, as you build the program, the processing may become more and more complicated. The more complex the process, the more time it takes to process it.

Using a library also has the advantage of making the program lighter because it organizes complex processing neatly to some extent.

Language ranking used for machine learning

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So which languages ​​are most commonly used for AI development? Here are eight popular languages.

  1. Python
  2.  R.
  3.  Julia
  4.  JavaScript
  5.  C++
  6.  Java
  7.  Haskell
  8.  Matlab

I will explain below.


Python has various libraries specialized for machine learning, and is a language that has gained a high share in fields such as AI development and machine learning. In addition to AI development, it can also be used for application development and game development.

Also, because the code is simple, it is recommended as a programming language for beginners to learn for the first time.


The R language is a programming language specialized for statistical analysis. It excels in data analysis and output to graphs, and is attracting attention along with Python. It will be positioned as an indispensable language for occupations such as data engineers, data scientists , and data analysts.

However, since it is not a general-purpose programming language like Python, a high level of expertise is required to master R. It also has the disadvantage of being slower than Python.


Julia is a programming language specialized for technical computing. While maintaining the versatility of Python, it has greatly improved convenience and speed compared to conventional languages, making it easier to use.

Julia is a scripting language, but it is fast and has a simple syntax. It can also be used from Python and R language libraries.

A script language is a programming language that is highly readable and can be written simply among the codes used in development. In contrast to the conventionally used compiler language, which is difficult for humans to understand, the script language improves the readability to a level where even if a human reads the code, the program can be understood to some extent and can be processed. increase.

On the other hand, there is also a disadvantage that awareness is low and there is little information about language and technology.

4. JavaScript

JavaScript is a programming language that can handle variables, function arguments, and return values ​​on websites by assuming types at runtime. It can be used to create web applications, and it is characterized by a wealth of work content.

In addition, libraries such as “Keras.js” and ” TensorFlow.js ” for utilizing AI from the browser have been released.

Therefore, it is useful when you want to use a trained machine learning model from a web browser.


C++ is a programming language characterized by high-speed operation.

It is also an object-oriented extension of the C language, and is designed to enable more efficient programming. Various extended functions have been added to improve development efficiency compared to C language.

Roughly speaking, object-orientation is to express what to make and how to make it as if assembling “things” and let the computer operate.


Java is a programming language that can be used in any environment without depending on the OS.

Java is a popular language all over the world, and because it is platform-independent, it can be run on any OS, including Windows, Linux, and iOS.

In addition, Java has a machine learning library called Java-ML, so it is also suitable for AI development.

7. Haskell

Haskell is used in systems that require security, such as financial systems, stocks, and foreign exchange trading, as it has the characteristic of being extremely bug-free.

However, unlike other programming languages, it does not have a convenient library, and it is a purely functional language, so it is also a language that is difficult to learn and use.

A pure functional language has the property that once a variable is defined, it cannot be reassigned, and if the same argument is specified for a function, the result will be the same no matter how many times it is repeated.

8. Matlab

Matlab is a programming language with strengths in scientific computing and numerical analysis.

It can do various things such as function and algorithm development, matrix calculation, GUI, etc. It is used in automobiles, financial engineering, robots and artificial intelligence.

However, since it is a paid programming language, you must purchase a license to use it.

Comparison table

Degree of recommendation number of projects Ease of learning Abundance of teaching materials Number of supported libraries

What is Python that is often used for machine learning development?

Introducing Python, the most popular programming language for machine learning development today.

The TIOBE Programming Community index publishes the popularity ranking of programming languages, and Python is currently number one. The reason for its popularity is that it is not only easy to use, but also that the language has evolved to be easier to use in the fields of education and science, and that it has been used in various fields with financial support from companies.

Python is a very versatile programming language that can be used for AI development, application development, game development, data analysis, website creation, etc. Therefore, by learning Python, you will be able to play an active role in a wide range of fields other than AI development.

Machine learning language library

As introduced above, a library refers to programming that allows anyone to easily use a series of highly versatile processes.

By using the library according to your purpose, you can easily design and execute the program without creating the program from scratch.

[Must-see for beginners] How to learn a programming language by yourself

How to learn a programming language by yourself for beginners,

  1. Basic learning
  2. Applied learning

I will explain this in two parts.

Basic learning

The first is basic learning.

Programming school

The first way is to go to programming school.

The advantages of learning at a programming school are that it is difficult to get frustrated, you can learn efficiently according to the curriculum, it is advantageous to find a job or change jobs, and you can ask questions immediately.

If you feel uneasy about studying alone, I recommend going to a school.


The second way is to study from books.

There are various books for learning programming languages, from beginners to advanced users, and you can find the book that suits you.

Recommended for those who want to learn at their own pace.


A third way is to read papers.

The paper is written by a professional researcher, so there will be a lot to learn from reading it.

Online courses/sites

The fourth method is to use online courses and sites.

The advantage of online courses and websites is that you can learn at your own pace, just like you would with a book. What is different from books is that some courses have a fixed curriculum.

Recommended for those who want to study in their spare time but are not good at making study plans.

Applied learning

Next is applied learning.

Acquire knowledge of mathematics and statistics

The first step is to acquire knowledge of mathematics and statistics.

When dealing with AI, knowledge of mathematics is essential. It can be said that knowledge of mathematics is necessary when programming system construction and implementation such as speech recognition and image recognition.

Artificial intelligence needs to handle a lot of data, and high school/university level knowledge of mathematics such as differentiation and integration, as well as knowledge of statistics, are required.

Get hands-on experience

And the other two is to get hands-on experience.

Practical experience can be gained through internships.

Some knowledge can only be acquired through hands-on experience. An intern can acquire such knowledge.


In this article, I explained what machine learning is, and recommended languages ​​and study methods for the programming languages ​​used for machine learning.

Currently, the market value of the AI ​​industry, where machine learning and programming languages ​​are important, is rising. As AI becomes more familiar from now on, knowledge of machine learning using programming languages ​​will be advantageous in finding a job or changing jobs.



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