Python ML

Have you realized that AI isn’t just a buzzword but an undeniable fact of the day? In 2020 solely, there appeared over 2,600 AI startups on a global scale, with first place taken by ML apps. And now this trend is evolving further, with the expectation to reach the milestone of $1.5 trillion by 2030

But the question is which programming language will be compatible with ML the best? Though experts are still debating on this, we consider Python the best option for all. Why is Python best for web development? The great ecosystem of Python ML libraries, clean code, cross-platform usage, and efficient work with large volumes of data are among the key reasons.

So, if you’re ready to implement AI for the sake of your web app’s speedy data handling, continue reading our piece. We’ll explain to you why AI programming with Python is a good idea for web solutions. Clear up your doubts!

ML libraries and frameworks in Python

What was priorly done manually, by human hands, now is done automatically by AI, in higher volume and with fewer efforts. Particularly, Artificial Intelligence using Python has become the crucial solution in the speedy processing and analyzing tonnes of data. And it hadn’t happened without Python ML frameworks.

The collection of libraries, with the pre-written code pieces, is the number one reason why Python has gained immense popularity. With these modules, you can construct your web functionality like puzzles, resulting in the specific actions that will be performed by users. 

Are you looking for the best Python ML library? It all depends on your aim. For your ease, we’ve gathered the most used libraries in the following table:

Saving a lot of developers’ time, each ML library in Python provides effective tools to access, process, and transform data into the required format.

Advantages of Python for web development

Though intelligent data handling is the decisive factor in favouring Python for Machine Learning, it’s not the only one. Go on learning the other pros below.  

Ease of use thanks to clear code

Have you heard about Python’s clarity, straightforward syntax, or easier entry barrier for developers? We can confirm that all of this is true. That’s why this programming language is so widely welcomed! 

What does it mean to you, a business owner? Well, you’ll have a broader talent choice when it comes to hiring devoted tech specialists for building your Python ML-based app. Moreover, you’re likely to reduce the time-to-market because of Python’s vast community, extensive documentation, and overall code simplicity. Isn’t it attractive?

Flexible usage on different platforms 

Another notorious reason in favour of Python for developing web solutions with AI is its flexibility. This programming language can be used independently or in combination with others. It also gives an opportunity to recompile the source code, which means any changes will be quicker represented on the web version. And, finally, Python can be interchangeably implemented for various platforms, and you won’t be limited to popular Windows, macOS, and Linux.

The cross-platform usage of Python makes it a good fit if transferring processes from one platform to another or running the code on different platforms makes sense to you. 

Splendid visualization choices

Hope you carefully read our discussion of Python ML libraries, and now we’ll add a new layer to their importance. Some of these libraries are wonderful tools for data visualization, which is one of the most crucial tasks for AI developers. What’s the value of all that if the data isn’t represented in the perceivable format for human users? That’s it!

With Python, this task becomes easier as you’ve got such excellent instruments as Matplotlib to create histograms, charts, and other visuals for better data comprehension.

Perfect compatibility with APIs

The programming language’s adaptability to APIs is one more determining factor you should keep in mind while selecting the tech stack. In this regard, Python is perfectly suitable for this role, being designed for automating programming routines.

Particularly, you can seek automation by making your web solution run in different OSs simultaneously with relatively minor changes in the source code. Isn’t that a miracle to save your developers’ time so tangibly? Just think… It’s already worth using Python for AI-based projects.

Smart data handling and analytics provided

We’ve already talked about easier data visualization with Python, and now it’s time to cover its data analysis potential. In other words, why Python is loved by researchers, statisticians, and developers? It’s good for data manipulation (collecting, processing, analyzing, sharing, etc.), calculations, and query solving.

What’s more, thanks to diverse APIs and Pandas profiling, you’ll decrease time and effort in preparing clear analytical reports, which will help your business make data-driven, or deliberate, decisions.

Fintech examples of Python and ML in web development

It all sounds good, but you might want to hear some examples of how the blend of ML with Python works in practice. As Patternica is primarily specialized in fintech software development, we’ve decided to search for illustrative cases in this industry:

  • Investment platforms—market research and predictions;
  • Insurance claims processing—process automation;
  • Autonomous decision-making—independent intelligence reads prompts and executes actions;
  • Risk management—loss minimization;
  • Fraud detection—safety of using a platform and data protection;
  • Insights generation—smart data handling;
  • Chatbot assistance—high-quality service to users… etc.

If translating it to the brand names, the most prominent Machine Learning Python program examples are Venmo, Robinhood, and Anaconda.

​​Use Python and ML to build technologies of the future

Are you now clearly seeing how Python and AI do their job in bringing more efficiency to your business? Hope yes, and the only remaining question on your side should be—how to develop an AI app using Python. You’re in the right place! Contact Patternica, and we’ll find the proper way to implement Python and ML for your web product.

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