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Golang and Machine Learning

Victor BjörklundVictor Björklund • Updated March 8, 2022

Golang is a programming language created by Google back in 2007 to solve the issues Google were having. They needed a language that was easy to understand and write yet powerful enough to solve compute intensive problems and large-scale data processing. Golang was their answer to that challenge. In this article, we will explore why Golang is increasingly becoming a choice when it comes to implementing machine learning.

As mentioned previously Golang is the answer to Google's challenges of having a language that is easy to understand yet powerful. Google was, and still is, using Python a lot and it’s a language famous for being easy to understand and code in which benefits speed of development. However, Python is also too slow for some tasks and can be difficult to scale at Google scale. They were also using C and C++ for resource intensive tasks since those languages can create very efficient applications. The challenge with C and C++ however is that it’s very low-level which makes it difficult to understand and also increases the risks of bugs.

Golang can be called a compromise between C++ and Python because it’s relatively easy to understand and write yet very powerful. In contrast to C++ it has a garbage collector which means that it simplifies memory management considerably at just a slight cost of performance. And in comparison to Python it often can run much faster and scale more efficiently.

Is Golang better than Python for machine learning?

Yes, in many cases it is. Golang outperforms Python when it comes to scalability and performance. In benchmarks Golang often performs up to 50% better than Python. One of the advantages of Golang is that it is a compiled language. This means that the code is converted into machine code that can be run on a computer. This makes it faster and more efficient than some other languages, which can be interpreted. This makes Golang a good choice for implementing machine learning algorithms, which can be computationally intensive.

However, performance and scalability are not the only factors when it comes to machine learning. The reason Python has become so popular for machine learning is the large ecosystem that grew up around machine learning and python. Golang already has several libraries around implementing machine learning but it will take time before it reaches the same level as Python.

At this point in time I would say Golang is a better choice for machine learning if the rest of your application is already using Golang and the algorithm you need to use already has a library in Golang.

In conclusion, Golang is a good choice for implementing machine learning algorithms. It is a fast and efficient language that has several libraries that are useful for machine learning.

Last Updated on March 8, 2022 by Victor Björklund
Victor Björklund

Victor Björklund

Victor Björklund is a full-stack developer and the founder of JawDropping.io. He has experience with Node, Svelte, React, Python and Elixir. At the moment he prefers to build amazing things using either Elixir or Svelte (This site is built using Svelte and the backend is using Elixir).

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