These days, AI programming has gone far beyond pure software or hardware development firms. Companies within most demanded verticals, like e-commerce, real estate, healthcare, and more, start adopting AI.
Python and Golang are the most popular programming languages for AI. As a company that has worked with both—we know it can be difficult to choose the right one.
Recently we have examined Golang web programming capabilities comparing it to other languages. You may check our discoveries as for Golang vs Node JS, Go vs Ruby, and of course, Golang vs Python comparison.
Now, it’s time to see which language, Go or Python, is better specifically for AI programming.
What Python brings to AI programming
You can hardly consider any programming language perfect, but certainly, Python has its strengths in the context of AI. Here are the most significant ones:
Extensive set of libraries
Python libraries help engineers build new algorithms (LightGBM), do model prediction (Eli5) and datasets processing (Keras), work with complex data (Scikit-Learn), and more. Not to mention Tensorflow, the most popular open source library used for many of Google’s machine learning applications.
Well established community
The community and the ecosystem around Python are vibrant and active. According to GitHub annual statistics, last year the global Python community sent over 1 million of pull requests. Community contributes much into creating new libraries, updating documentation, and extending toolset.
Python is an accessible programming language, and it keeps gaining more ground. For businesses, accessibility means a vast market of Python experts. Besides, this language is widespread. Recently it’s been ranked by the Institute of Electronic and Electrical Engineers as the top programming language of 2018.
However, while Python is sometimes referred to as the best programming language for AI, it has its disadvantages.
Bad for large-scale engineering
When it comes to work involving a few hundred programmers, Python clearly losing to Golang scalability. It’s also challenging to use Python if you require a very ordered and disciplined way to do programming. The same is true when you are going to deploy very complex AI systems.