Python is the Best Friend of AI! Here’s how

by Josh Biggs in Software on 16th December 2018

Taking a look at current business trends, AI seems to be worth investing in. Tech enthusiasts consider it one of the most advanced fields of computer science as it has a great power to liberalize, streamline, and simplify complex operations.

Within a few years, Python has grown manifold such that techies swear by it on the grounds of programming. Due to its growing influence on web development and automation, no longer does Python consider only a programming language .

If you are new to Python, other languages, for example, LISP, Prolog, Java, Python, C#, etc., can solve the purpose.

Make sure you consider the availability of web developers and ease of code while deciding on a language.

But what makes Python stand above others. The language is based on OOPs, which makes it a high end interpreted programming language that can fasten the development of applications. Its growing user base accounts for its ease of learning, scalability, and adaptability of Python.

What makes it a high-grade language is its libraries that take you deeper into a web app, mobile app, IoT, data science or AI.


No matter whether your company is big or small, Python is likely to uplift your web development projects in many ways. As I said earlier, this language is up from programming as it has come up with its new versions in the form of artificial intelligence, machine learning, natural language processing and data science.

Many would already have heard these technical terms; only some would be aware of their meanings, Deep learning comes under machine learning, which is a category of artificial intelligence. To put it simply, AI is the intelligence of any machine that provides you with optimal solutions.

Machine learning is a result of algorithmic equations capable of analyzing big data processes to help organizations make informed decisions. Deep learning is not much different from Ml; however, it can do many other things. Its layered structure of algorithms has the capability to offer you business insights that can optimize your business architecture.

Designing of the structure involves the neural network just like the human brain. Therefore, it acts like a standardized framework that can help you learn multiple levels of representation to deliver business related insights.

Why combine Python with ML?

Reading this post, you would be wondering that why the heck you need to bother of considering Machine Learning with Python.

Here are five top reasons.

  1. Less Code — The world of AI revolves around AI algorithms, and Python simplifies it to make it easy for developers to implement it in testing. Moreover, developers will be able to write code and execute code easily. You would be surprised to know that the language can use the same logic with a one-fifth of code is needed in other OOPs languages. Developers can check their code during application development, and make changes up front.
  2. Storehouse of libraries— What makes Python different from others is its libraries that cater to all types of project requirements. Opting for Numpy makes your computation faster while SciPy is a good option for advanced computation, and Pybrain supports ML. Coding has become way easier through a Python library-‘Modern Approach’.
  3. Support — Being an open source platform, Python fastens the overall development process. You can join online forums, for example, Python Newsgroup, Python IRC channel, etc., to take help in case you stuck somewhere.
  4. Platform Friendly — The flexibility of Python is worth considering. It provides you with an API no matter what language you use for application development. You just need to change your code to run on a new OS. Now, developers need not spend time testing on different platforms.
  5. Flexibility — Since Python is versatile, you can decide between OOPs approach and scripting, per your requirements. Its backend process is highly straightforward; therefore, developers can easily co-relate different data structures in an effective way. You do not need to battle with different algorithms as Python allows you to check code in the IDE.
  6. Dynamic — Python is ideal for most developers due to its versatility and flexibility. Being one of the most preferred languages, it has led to the growing demand for Python developers. The irony is you can easily find Python developers; however, LISP or Prolog programmers are hard to find.

AI and Python are likely to amaze us in the future by bringing new possibilities to life in the world of development. Non-programmers can even begin from scratch to start with Python and make it part of their application development lifecycle.




Categories: Software