I'm a Systems Reliability and DevOps engineer for Netdata Inc. When not working, I enjoy studying linguistics and history, playing video games, and cooking all kinds of international cuisine.
Go is a great language for network programming, and it’s got a lot of adoption there.
In fact, it’s actually replacing Python there at a reasonably fast pace in terms of product lifecycles (and this is the timescale you should be looking at, it is very rare for an existing project to switch languages, so any uptake is in the form of truly new development).
However, Python is quite simply better for rapid prototyping, has a somewhat shallower learning curve, has 20 years more maturity, and has a much larger ecosystem. Given all of this, it’s going to continue to be the language of choice for code-monkey type programmers and people who program as a side-effect of their job instead of a primary function of their job (such as scientists and mathematicians) because it all means it’s easier to work with on average.
I'm a Systems Reliability and DevOps engineer for Netdata Inc. When not working, I enjoy studying linguistics and history, playing video games, and cooking all kinds of international cuisine.
I’m not particularly well versed in ML myself, but most of the people I know who are and who work with Go fall into two groups:
Those who complain about golearn and the TensorFlow bindings for Go (those seem to be the two most popular options) because of their reliance on cgo and the issues that brings along, and tend to use other languages for ML work (mostly Python from what I’ve seen).
Those who use gonum to just write the ML algorithms directly instead of relying on a library that includes them (this obviously works, but requires a higher level of understanding of the algorithms than most people have).
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Possibly you’re looking in the wrong places?
Go is a great language for network programming, and it’s got a lot of adoption there.
In fact, it’s actually replacing Python there at a reasonably fast pace in terms of product lifecycles (and this is the timescale you should be looking at, it is very rare for an existing project to switch languages, so any uptake is in the form of truly new development).
However, Python is quite simply better for rapid prototyping, has a somewhat shallower learning curve, has 20 years more maturity, and has a much larger ecosystem. Given all of this, it’s going to continue to be the language of choice for code-monkey type programmers and people who program as a side-effect of their job instead of a primary function of their job (such as scientists and mathematicians) because it all means it’s easier to work with on average.
Herd about Artificial intelligence? Or can you mention a widespread go package for ML.
I’m not particularly well versed in ML myself, but most of the people I know who are and who work with Go fall into two groups: