C++ is one of the oldest object-oriented programming languages. Bjarne Stroustrup built this language to fill the void of the C programming language. A few years after its launch, C++ became very popular, and millions of developers continue to use it for their builds.
C++ is the second most widely used programming language in Machine Learning. C++ is also used in machine learning and developing projects, including artificial intelligence and robot locomotives.
I just answered your query, but let me explain it to you. Trust me, it’s worth your time.
Why C++ is still used in Machine Learning
Though C++ isn’t the ideal programming language for machine learning, some features make it capable of competing with modern programming languages like Python.
Performance
You might be familiar with the fact that C++ is a static programming language. If you don’t know what a static programming language is, then let me brief you about it;
A static programming language allocates memory at compile time and performs all the primary operations at compile time.
Since C++ is a statically typed programming language, it offers efficient and quick run time compared to modern programming languages like Python and other dynamic programming languages.
Besides this, C++ won’t pop type errors during RunTime, which makes it a neat and time-efficient programming language.
In terms of performance, C++ sometimes outperforms Python, which is why it is the second most widely used programming language in Machine Learning.
Simplicity
If you ask a programmer, they will say Python is the easiest yet powerful programming language. Even if you ask me, I’ll say something similar. Undoubtedly, its simplicity is why Python is the top-rated programming language right now.
But what about the second most straightforward programming language? Is it Java? No. It’s C++. According to the report published by Vision Mobile in State of the Developer Nation Q1 2017, over 43% of developers prefer C++ for its simplicity and efficiency in Machine Learning.
Usability
We are all familiar with C++’s age. It’s quite an old programming language; every graduate learns it in their institute. C++ has been in the market for more than three decades. Everyone who is into development at least has some knowledge of C++.
The popularity of C++ makes it a pervasive and universal programming language. This allows beginners in the Machine Learning Industry to create projects using C++.
Fun Fact: Thanks to its secure architecture, C++ is preferred chiefly when building chatbots in machine learning. -Vision Mobile
C++ Machine Learning Libraries
Since you have asked whether C++ is used in Machine Learning, this indicates that you are planning to start developing Machine Learning projects using your C++ knowledge.
Before you proceed, let me tell you that Machine Learning requires complex programming. You might have to write thousands of lines of code to create a simple ML application.
This sounds tiring, Right?
But what if I tell you that some C++ experts have already built dozens of C++ libraries, making its implementation in ML relatively easy?
You can use those pre-built libraries to make your project less tiring and more efficient. In this, I’ll talk about two viral libraries of C++:
MLPack Library
Shark Library
MLPack Library
MLPack is an open-source Machine Learning library that contains the following algorithms:
Python Binding
Julia Binding
Command-Line Programs
MLpack is preferred because it provides fast and scalable solutions that can easily be implemented in large-scale machine-learning applications. MLPack library is mainly used for its algorithms.
Note: Refer to its official website to learn more about the MLpack library.
Shark Library
Shark Library was built to provide algorithms for Supervised Learning like:
- Clustering
- K-mean
- Neural Network
- Linear Regression
Apart from this, Shark Library also provides support for Linear Algebra and Numerical Optimization.
Shark is preferred because of its modular architecture and comprehensive support for mathematical-related tasks.
Note: Refer to Shark’s official website for documentation.
Different Fields where C++ is still used
Machine Learning is not the only advanced field where C++ is used; there are several others:
Artificial Intelligence
Artificial Intelligence is a vast domain, and C++ can’t fulfill all its requirements. C++ is used explicitly in AI Game Development. According to the Vision Mobile report, 29% of developers prefer using C++ while developing AI games.
Robot Locomotion
C++ is used in 27% of Robot Locomotion projects. This language is preferred because it’s a static programming language and doesn’t pop the RunTime error, which allows developers to debug their Robot Locomotion projects more effectively.
Network Security
As mentioned above, C++ has a robust architecture, which makes it entirely attack-proof. After Python, C++ is among the most secure programming languages, which is why some Network Security projects are developed using C++. Currently, 26% of Network Security projects have C++ as their primary language.
Conclusion
Though C++ is quite an old programming language compared with modern languages like Python, it still can fulfill the requirements of modern industries like Machine Learning and Data Analysis. It is still among the most actively used programming languages in the ML industry.
Thus, if you plan to make a career in Machine Learning and don’t have enough knowledge of languages like Python, you can still reach the pinnacle of your career using C++ as your primary programming language.
However, it is recommended that you learn other programming languages to become compatible enough to work on Machine Learning projects. You can check platforms like Udemy, Coursera, and Edx for free access to courses taught by industry experts and professionals. A few courses and several hours of practice will make you an expert in any programming language.