Python: The Preferred Language for AI and ML Development

After a time, perhaps, the second fastest-progressing thing on the planet is AI-ML! It might seem like an overstatement. But we believe AI-ML is a technology duo evolving and proliferating more rapidly than any other. However, a massive ship has many parts, components, and propellers that enable its movement. AI-ML also has several intelligent technologies working behind the scenes and fueling its growth. AI ML development with Python is one of them!

As we all know, Python is an interpreted, high-level, and object-oriented programming language with dynamic semantics. It has been around for over three decades and forms the base of many popular applications like Pinterest, Spotify, Uber, Reddit, etc. All these applications use AI-ML to varying extents. But why is Python such an excellent choice for AI and ML development? Let’s find out the most significant reasons.

6 Reasons Reasons why AI ML development with Python:

Python has everything an AI-ML application requires. Let’s look at some prominent features and functionalities Python offers to know why AI ML development with python is important.

1. Low Entry Barrier

Dealing with AI-ML refers to dealing with extensive data that requires effective and meaningful processing. The low entry barrier enables data scientists to choose Python and use it for AI development without spending time and effort learning it.

Python programming is similar to routine English. Hence, it represents a softer learning curve. It has a straightforward syntax allowing you to work comfortably with sophisticated systems with well-defined relations between the system and elements.

2. An Extensive Library

Another significant reason Python is preferred for AI and ML development is its extensive library. ML demands continuous processing. Python libraries support this need by enabling you to access, handle and transform data. Some widely used Python libraries for AI-ML development include Pandas, TensorFlow, Matplotlib, PyBrain, NLTK, etc.

3. Platform Independence

While offering the convenience of use, Python also provides versatility. It refers to Python’s capabilities of running on platforms like Linux, Windows, MacOS, Unix, etc. Transferring the process from one platform to another requires developers to implement many small-scale changes and modify some lines of code to build an executable code form for the platform they’ve selected. They can leverage packages like PyInstaller to prepare the code to run on various platforms.

4. Excellent Visualization Alternatives

Technologies like AI, ML, deep learning, etc., have been invented to simplify things for human beings and represent data in an easily readable format. For that, developers require outstanding visualization tools that are available with Python. Libraries like Matplotlib enable data scientists to build histograms, charts, plots, etc., for better comprehension, visualization, and presentation of the data involved.

5. Easy to Read

Python is an easily readable language. Hence, every Python developer can understand their counterpart’s code and change and share it. Such levels of transparency and clarity enable a more efficient exchange of ideas, algorithms, and tools between AI-ML experts.

6. Flexibility

Python offers flexibility that allows developers to choose various programming styles individually or in each other’s combinations. Some programming styles include the below.

• Functional Style: The functional style is also termed declarative, as it declares the operations to be performed.
• Procedural Style: The procedural style involves proceeding step-by-step. It is often used for sequencing, modularization, iteration, and selection.
• Imperative Style: It consists of commands that describe the way a computer should perform a particular set of commands. This style allows you to define the chronology of computations that take place like a change in the program state.
• Object-Oriented Style: It is based on two concepts – class and object, in which similar objects form classes. However, Python doesn’t support this style fully, as it cannot completely perform encapsulation.

Build robust, scalable, and incredible AI-ML applications on Python with Fidel Softech. We are a trustworthy AI-ML app development company with several years of experience working on Python and developing AI-ML applications for diverse business domains. Our proficiency in using Python and capabilities to optimize its features and functionalities enable us for value-driven AI ML development with Python.

Our AI-ML developers can customize the application to suit your needs and provide extensive support, including maintenance, upgrades, and regular updates. So, while developing an excellent AI-ML application, you can stay on top of its performance.

Please email us at sales@fidelsoftech.com to learn more about our AI ML development with Python.

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