Golang Vs Python For AI Development

#go #python

These days, AI programming has gone far beyond pure software or hardware development firms. Ecommerce companies, real estate, healthcare and so on are already started adopting AI. AI applications help to improve user experience, customer interaction, healthcare accessibility, Financial planning, purchase experience and so on. With the use of machine learning, logical reasoning and self correction, it is possible to mimic human intelligence and human knowledge. Neural networks create high-level abstractions for many industries and disciplines. Ai

Python and Golang are the most popular programming languages for AI. Choosing the best one between two is a critical task so here we came with a detailed guide- golang vs python for AI development. Before digging to the comparison, let us see overview of each language.

What Is Golang?

Go is an open-source programming language developed by Google. It is a statically typed compiled language that supports concurrent programming and allows running multiple processes simultaneously. Go has garbage collection that itself does the memory management and allows the deferred execution of functions.

Also it delivers great performance with lightning speed and Go Web Framework is one of its kind. It has built lots of robust web apps and mobile apps.

Features Of Golang-

Golang is an open source language created at Google
It is a compiled language including great libraries, concurrency support.
Also it includes garbage collection called goLand
Code is Golang is easy and readable
Easy concurrency support via goroutines
Package management
Static typing
Features powerful standard library

What Is Python?

Python is a popular and potential programming language that is used by developers to build robust server-side development. It has built-in data structures, combined with dynamic binding and typing, which makes it an ideal choice for rapid application development. It can be used for cognitive technologies like machine learning, artificial intelligence and so on. Because of the versatility and easy learning, Python has retained its first position in IEEE spectrum. It includes various libraries that supports a particular niche like mobile apps, desktop apps, cognitive technologies etc.

Features Of Python-

Python language is easy to learn, and read
It has an ability to run various hardware platforms and using same interface.
This language offers an ideal structure and support for large programs, and automatic garbage collection.
It supports interactive mode of testing and debugging, and also offers a high level dynamic data types and dynamic type checking
Python language can be integrated with Java, C and C++ programming code
It has a simple and minimal syntax, offers high performance and fast compilation times
You can include low-level modules to the Python interpreter.

Golang Vs Python For AI Development-

Advantages Of Golang For AI Programming-
1. Superior Error Handling And Easier Debugging-
As the name suggests AI must mimic human intelligence. In its result, input and output must be simultaneous because of which error handling must be quick. Downtime due to debugging cannot take long. Golang has a variety of good machine learning, reinforcement learning and deep learning libraries focussed on all parts of pipeline. Some of them are for natural language processing, tensor operations and even a GPU accelerated deep learning stack. The resultant app are refined and functionality rich.

2. Speed And Accuracy-
Concurrency model and simple syntax helped to improve the speed of language. It allows to manage number of concurrent requests simultaneously. With accuracy that tops the list Golang source code is also fast, thread ready, easy, clean, compiled and simple. Also, it has a huge number of support of libraries for Natural language processing, machine learning, data analysis, extraction, processing and visualization. This makes it appropriate to develop comprehensive real world AI applications.

3. Good At Scale And Computations-
Golang scales and performs well within large-scale projects. Speed is one more reason to use Golang for AI programming, particularly for math computations. Golang is 20 to 50 times faster than Python in case of complex math problems.

Know the best practices for golang at- Top 11 Golang Best Practices For 2020.

4. Minimalism And Good Code Readability-
Most of the algorithms stick to a minimalist approach, this enables developers to write a readable code after algorithm implementation. But minimalistic approach can be a weak point too, in case of where there’s a need for recursive algorithms, that can run slower because of the absence of tail-call optimization.

Golang’s Downsides For AI Programming-

1. Need For Deep AI Expertise-
Some of the Golang advantages for web development can play against it about AI programming. For example, default multithreading works good for Golang web development. But using multithreading for AI purpose needs skilled Go developers with deep expertise in data science.

2. Golang Toolkit Extension In Progress-
Go has its libraries for AI and it can cover the most necessary purposes, but the toolkit is not that much extensive. Inshort, it’s in the process of extension with Golang community itself. So far, Golang developers have performed about 285K pull requests globally.

Advantages Of Python For AI Programming-

1. Extensive Set Of Libraries-
Libraries of Python helps developers to build new algorithms, do model prediction, and datasets processing, work with complex data and so on. Tensorflow is a popular open source library used for many Google’s machine learning applications.

2. Strong Community-
Community and ecosystem around Python are vibrant and active. According to GitHub’s annual statistics, Global community send more than 1 million of pull requests. There is a huge community support for creating new libraries, updating documentation and extending toolset.

3. Python As A Language Is Accessible-
Python is an accessible programming language. For businesses, accessibility means vast market of Python experts. Apart from all this, Python is widespread. It’s been ranked by IEEE as a top programming language.

Also know the details of use of Python in finance, analytics and artificial intelligence at- Using Python in Finance, Analytics and Artificial Intelligence.

Know the amazing new features of Python 3.10 at- Must Know Features Of Python 3.10.

Python’s Downsides For AI Programming-

1. Not Good For Large Scale Engineering-
Python is losing to scalability for projects that involve a few hundred programmers. If you need a very ordered and disciplined way to do programming, then it will be challenging with Python. It is also challenging while deploying AI systems.

Know more at- [https://solaceinfotech.com/blog/golang-vs-python-for-ai-development/]