Launched in 2009, Golang recently turned ten. Programmers become more productive because this language developed by Google. Golang's purpose was to create a language that would eliminate the so-called “extraneous garbage” of programming languages like C++. It provides the capability of compiling to machine code, the ability of run-time reflection, and provides the convenience of garbage collection.
The question is: Will Golang replace Python? No, it won't.
Has been widely used for numerous purposes, it's hard for Python to become obsolete. It is a programming language that compiles a thousand components from individual modules to packages of the entire development. Python also has a strong community that promises to keep it alive for the next few decades. Being tested for multiple numbers of environments, it was found to be easy for beginners to work with Python programming and has been deemed favorite amongst young developers. Go language outperforms Python while writing server-side scripts. Thus, when looking for ultra-performant concurrent services that have quick deployment cycles Golang is said to outperform Python.
However, in recent times Golang and Python have been termed as the most popular languages that are perfect for AI professionals. As organizations work with both these languages, it can be challenging for you to come up with a stern solution.
Advantages gained from using Golang for developing AI.
High scalability and computation: Golang has a higher potential in scalability and performance as compared to Python. The idea of using Go is because of its high speed as compared to the speed of math computation. For instance, it can cope with complex math problems of up to 20-50 times higher and much faster as compared to Python.
Vast AI purposes covered by Golang: Although Go offers small libraries it is consistently growing thus, addressing a large range of AI purposes. Go libraries such as GoLearn (data handling), Goml (passing data), and Hector (binary classification problems) are some of the libraries that serve AI and its applications.
Offers a good amount of code readability: Algorithms used in Go offers a minimalist approach allowing developers to easily create readable codes.
Ease of usage of Go libraries by Go developers: Most of the Go developers do not need to opt for libraries written in other programming languages. The core advantage of having libraries in Go is that it gives the AI professionals working programming with Go a developer’s comfort.
The benefits of using Python for developing AI.
Multiple numbers of libraries: Multiple libraries can now help AI engineers build new algorithms, conduct dataset processing, do model processing, work with the most complex data, and many more other functions. Not to forget, TensorFlow is one of the most popular libraries (open source) that is utilized for many machine learning applications of Google.
Python as a language is accessible: In business terms, language accessibility simply means having a vast market of experts in Python programming. Moreover, as we’re aware these programming languages are widespread across the globe.
Strong community: Python has a well-established and strong community. Based on GitHub’s report in 2019, there was nearly 1 million pull request sent over worldwide. The community tends to contribute toward creating new libraries to extending toolset and updating documentation.
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