Developing AI Web Applications in Python

Did you know!

• Artificial Intelligence holds a compound annual growth rate of 40.2% from 2021 to 2028.
• The revenue forecast of AI in 2028 stands at a whopping $997.7 billion.
• Business leaders firmly believe that AI will become fundamental, and 94% consider it will create multiple innovative opportunities.
  

Artificial Intelligence (AI) has long been an essential part of any business that relies on data, analytics, and automation to run its business processes and operations. 

AI provides automated decision-making based on the evaluation of big data. However, when looking for AI development, a significant aspect is choosing the right programming language besides the right team. 

Python in Artificial Intelligence is a renowned option for software development projects. Notably, Python has emerged as one of the most popular programming languages for AI-related applications today.

In fact, Statista lists Python among the top programming languages for web development with a popularity of 48.24%. The infographic below offers insights into the chief languages preferred worldwide for web development.

Source: Statista - Top Programming Languages

Python in Artificial Intelligence offers multiple advantages over other programming languages such as Java and C++. The reasons why Python is best suited for Artificial Intelligence in web development are provided below:

• Python is open source
• Offers a massive amount of community support
• Libraries simplify the coding process
• New coders can learn with ease
• Minimal Coding Requirement
• Flexibility
• Compatibility

Let's explore these reasons in detail.

Python is Open Source

Source: The New Stack 

A significant benefit of using Python in Artificial Intelligence is that it's open-source. It gives developers access to hundreds of thousands of lines of code that they can use as reference, making it easy to learn how to write and structure code.

Anyone can contribute to an open-source project, meaning numerous others have tackled similar problems or shared your interests and language requirements. It means you can hire python developers who don't have to waste time building everything from scratch. Plus, by contributing back, people get a chance to make a reputation as a developer.

Offers a Massive Amount of Community Support

While other frameworks provide many libraries and a great ecosystem, it's hard to compete with Python's sheer popularity. Because it has been around for a more extended period, there are plenty of tutorials & resources available to learn how to develop apps.

Developers can search through everything from forums to case studies and example codes, making it easier to find answers and make connections. Joining a community like Stack Overflow helps you stay on top of industry news. 

In addition, relying on an already established network means that people are more likely to use software that has been tested & reviewed by thousands of other developers. It ensures reliable functionality that saves time when you use Python in Artificial Intelligence!

Libraries & Frameworks Simplify the Coding Process

Source: Slide To Doc

Some notable Python libraries include Spacy, used to parse and generate text, TensorFlow, which supports numerical computation with machine learning and NLP. Similarly, NLTK provides access to a large corpora of human language data and Gensim, a widely-used semantic modeling tool.

With tons of development tools and libraries, developers can save countless hours of coding time. Add its flexibility and rapidly growing community around it, and you have a recipe for an excellent language. It's hard to imagine why programmers would want to use anything else.

Python's reputation for minimal bureaucracy makes it easier to get a project off the ground, with AI development requiring intensive learning. You don't want any barriers getting in your way, which makes Python in Artificial Intelligence an invincible choice. 

New Coders can Learn with Ease

When people learn how to code, they often choose languages like Java or C++. While these are excellent choices, they tend to be much more complex than languages such as Python. The syntax of many coding languages can be pretty tough to understand.

Learning a new coding language takes time & effort. There are, however, some coding languages out there that require much less time to pick up than others. By learning Python first, you'll open yourself up to several different software development jobs on artificial intelligence platforms.

Using Python in Artificial Intelligence projects makes it much easier for new coders. Moreover, it is much easier to learn due to its clear-cut rules and simple structures.

Minimal Coding Requirement Saves Development Time & Cost

It will also allow you to develop programs using existing code libraries written in Java or C++. Developers can even introduce other coding languages like R and Swift. If nothing else, you'll come away with knowledge of two well-rounded programming languages under your belt: Java and Python. And that's worth something!

Many find Python more straightforward to read than any other high-level language because of its object-oriented programming features and its design philosophy that emphasizes code readability. Such simplicity comes from reducing complexity through procedural abstraction rather than eliminating all possible combinations of code execution states.

While explicitly made for internet applications, Python has many general-purpose application uses, including text processing (beneficial given large amounts of data it processes) and CGI web development.

Flexibility Ensures a High User Experience

One of Python's biggest strengths is its ability to incorporate data from many different sources into a single project. Though it's easy to use, any programmer with a good knowledge of C++ can pick up and create an AI utilizing this programming language.

Additionally, because Python doesn't have multiple versions, users don't need to worry about compatibility issues when using various software programs. It makes them one of the top choices for AI companies.

There are many options for programmers looking to enter into AI work in today's market. A developer's love of their work also plays a role. There are three main parameters checked by AI developers: imperative, functional, and logic programming. Notably, Python fulfills all of it effectively

High Compatibility Facilitating Complex Projects

It's a popular scripting language that can automate other systems and applications processes. Writing complex programs is beneficial as a general-purpose programming language, but it's also commonly used to build websites and web applications.

You can integrate Python with other services like Dropbox and use a variety of frameworks to get started quickly. Python in Artificial Intelligence is one of the easiest combinations to use. Mainly because novices don't need any previous knowledge about programming, nor do you need a compiler/interpreter set up. They can simply start as beginners.

Here are Few Important Use Cases of Python in Artificial Intelligence

Netflix: With the subscriber number standing at 182 million users, Netflix is a worldwide renowned app. The AI features of the app include data analysis, automating alerts, etc. Python has been used to integrate AI features into Netflix effortlessly.

Amazon: The worldwide renowned eCommerce platform leverages Python to develop its search engine and enhance its machine learning capabilities. Combining with Big Data, Amazon now offers more accurate recommendations to its client base.

Final Words

The artificial intelligence field has an exciting future. The world of AI is already changing our lives in many ways, & that's just scratching at the surface.

There are plenty of excellent communities and experts out there who can help you dive deeper into computer science and machine learning to understand what's the market.

Connecting with a Python development company for your applications will significantly benefit from its features, including easy-to-use libraries and concise syntax.