Why Python is the perfect choice for AI & ML project

With most companies using Artificial Intelligence and Machine Learning technology, it’s significant to use a programming language that reduces the code complexity and offers simple implementation. 

Though developers have ample opportunity to use different programming languages, Python gives them an edge over other available languages. Python offers a large number of libraries with simple and flexible tools, which makes the job easier. 

Plus, it is one of the leading solutions that can work for ML and AI. Python has gained an extensive advantage over different programming languages and is being used for different projects. You can hire Python developers to know more about compatibility. 

Let’s dive deep and look into what makes Python an ideal choice. 

1. Huge frameworks and libraries 

Building different ML and AI projects can be time-consuming. And at times, the coding process can be a complex one. However, many libraries are prewritten and compatible with Python, so developers prefer it over other languages. 

The libraries available in the stock make the process seamless for new developers. Developers can pick a library based on the need of the project. For instance, the Pybrain is used for machine learning, and Scipy is specifically used for advanced computing. 

Also, programmers can save a lot of time by using the approach, which is a unique library. 

2. Flexible platform 

Python is a highly flexible platform and is suitable for every purpose. The programming language offers the benefit of choosing between scripting and OOPS. Plus, you can consider recompiling the source code in project development. 

It’s easier to bring any changes, which saves time. Additionally, it allows the developers to choose from different programming styles, following which they can combine various styles to create better projects. 

The language is suitable for linking different data structures and offers perfect backend solutions for programmers. Moreover, it’s the most feasible choice for programmers who are often stuck between different algorithms – providing them with the power to check the code.

3. Its quite popular 

Python is quite popular among the developer community for creating projects. It’s one of the top programming languages, and most developers love to use it for simple stacks and tools. 

Moreover, it is one of the most commonly used languages for new developers. Developers can easily choose from the many Python packages available online. With a wide choice of packages, choosing the one for the project becomes simple. 

Leading companies have been using the language for years, so it’s the most preferred choice for the AI community. It is also the number one choice for developers who work on machine learning projects.

4. Platform-independent nature

Python has a platform-independent nature and that’s why most developers prefer the language. It makes the entire process of building solutions more seamless and simple. 

Developers can work on multiple platforms without errors. By tweaking the codes, they can make the applications ready to run or go live in no time. Additionally, they can run the apps on different OS. 

By choosing Python, developers can save a lot of time they otherwise waste on testing applications. The flexibility of coding is the main feature of Python. 

5. Better visualization options 

As discussed earlier, Python comes with a variety of libraries that are available online, and those libraries come with visualization features and tools. Moreover, when it comes to AI, the developers need to develop visuals for a project. 

They need to highlight the visuals for accuracy and attention. Plus, it plays a vital role in presenting the data. For instance, libraries like Matplotlib can be helpful for programmers and data scientists. 

It allows creating of different charts and histograms and – creating plots for data comprehension. The tools help in visualization and representation, which helps the developers to build better reports. 

6. Clear readability 

With Python, you will get the benefit of readability, which is an important aspect of technology. It is a simple language, easy to use, and beginners can change the code. 

Unlike other programming languages, Python is not complex. Besides, ease of use plays a vital part in exchanging ideas, algorithms, and tools. As a result, AI professionals can use the language to bring minor or big changes to the project at any given time. 

Apart from the readability, there are tools available to create an interactive design. The external tools can help in debugging and tab completion. It can also help in testing. Additionally, it also plays a part in facilitating the work schedule. 

7. Rapid development and community support 

Python offers the benefit of prototyping, and if the developers are familiar with stacks, it saves time. Also, the developers don’t have to waste time in the integration of AI. Most developers consider Python simple as far as readability and writing are concerned. You won’t need to learn the complicated codes. 

Python offers extensive community support – backed by experts and professionals in the field. Additionally, it provides the developers with all the essential resources they need to work on. 

New developers can work quickly and hassle-free. Besides, the experts are always preparing to rescue new developers if they are stuck with the project. In every phase of the development cycle, you can take the help of experts. 

Wrapping up,  

AI and ML technology is constantly evolving and bridging gaps between companies. Implementation and integration can help increase efficiency and productivity. 

Additionally, the use of Python for the two technologies is providing solutions to real-life problems. Plus, you can expect a customised user experience with Python. 

Community Languages Tips

The Latest Topics Developers Are Reading

What are the latest topics developers are reading? Some things change and others stay the same. When we looked at our data on what developers were reading in Q2, data and analytics, Jakarta, cloud-native, Kubernetes and Open Source topped the list.

In Q3 analytics (together with data) remained high on the list, but a few other topics emerged. The whole “shift left” movement is hot, as is security and anything related to “full stack”.

Here’s how we do the analysis. With 29 million unique readers every year, we decided to evaluate the data on from quarter to quarter. In this post, I’m also looking at Q1 to Q3.

Keep in mind the pageview comparisons provide insight into what developers are reading and interested in learning about. The tags used to collect our data are assigned by our editors and used to help readers search once they’re on our site. They aren’t keywords.

So, with that in mind, let’s take a look at what’s trending right now.

The Latest Topics Developers Are Reading:

Data + Analytics = Popular Reading

This quarter, we saw significant growth in the following topics: “data analysis tools,” which grew by about 3343% from Q1 to Q3, “data application,” showing 37% growth from Q2 to Q3 and 950% from Q1 to Q3, and lastly “augmented analytics,” which grew by 21% from Q2 to Q3 and 1108% from Q1 to Q3.

It’s no secret that our world is becoming increasingly data-driven. As this article series has discovered time and again, data and analytics dominate software trends.

One pivotal factor in data analytics is the use of Python. Python can wear many hats. Heavily used in back-end development, it’s also beginning to dominate algorithms, analytics software, and the entirety of a data project’s lifecycle. Python data tools can be found for data collection, data modeling, and data visualization.

As computer scientists get more and more involved in data science, they are using Python to write algorithms, explains Michael O’Connell, chief analytics officer at TIBCO. This is resulting in a major surge in Python libraries and data analytics tools based in this language. “Computer scientists and mathematicians are starting to blend,” he says.

Another term that saw tremendous growth this quarter, and this year, is the concept of augmented analytics.

augmented analytics growth

“In order to bring AI forward, we need to understand brain structures better,” O’Connell says.

This will help process and analyze data much faster.

“I think what people have started to realize is that time is very precious and continues to become even more precious. Data volume is increasing. The need for insights in real-time is increasing. So, the only way you can do that is through augmenting your intelligence effectively by building solutions that don’t give you the answer but provide you smarter ways of being able to slice and dice information.”

No matter your job title, whether you’re a developer, project manager, marketer, or something entirely different, any and every profession will benefit from smarter data collection, processes, and tools.

Automated Testing Topics Show Growing Interest

Interest in automated testing grew steady among readers over the last 9+ months. “Shift left,” a term meaning to ‘test early, and test often,’ has taken over the SDLC — developers are looking for more tools and frameworks that can easily integrate tests with minimal amounts of code.

This is where testing platforms like Selenium and Katalon Studio come in handy. These platforms allow testers to avoid manually writing tests. They can also create automated tests throughout dev environments.

Here’s a look at how these automation testing topic tags performed:

  • Automation testing tool grew over 60% from Q2 to Q3 and 1176% from Q1 to Q3
  • Selenium test automation grew over 23% from Q2 to Q3 and 1053% from Q1 to Q3
  • Testing frameworks grew 22% from Q2 to Q3 and over 641% from Q1 to Q3.

“The process of creating automation tests shouldn’t require writing extra code,” explains Jason Simon, (@jason_c_simon) freelance web developer, and tech writer. “Eventually, as we’re getting more and more code-free, this will not just be popular in test tech but in all parts of software development. The idea is to have business analysts doing a lot of the programming logic, without actually having to write a single line of code.”

 Automation testing tool grew over 60% from Q2 to Q3 and 1176% from Q1 to Q3 Selenium test automation grew over 23% from Q2 to Q3 and 1053% from Q1 to Q3 Testing frameworks grew 22% from Q2 to Q3 and over 641% from Q1 to Q3.

Simon predicts that in 2020, as testers write less and less code, the testing process will become more autonomous, with companies even adopting AI bots to automatically test new features. So basically, your test code will begin to automate itself. How cool is that?

The latest topics developers are reading on the Rise of Modern Security

Basic authentication and password management no longer cut it. The end of 2018 and early parts of 2019 were all about adopting basic security hygiene. But now, we’ve got to get more sophisticated and intentional about security — in all aspects of the development lifecycle.

This quarter, we saw topic tags such as “JSON web token,” grow over 190% from Q2 to Q3, “cloud security issues,” grow about 10% from Q2 to Q3 and 434% from Q1 to Q3, and “web vulnerabilities,” grow by 18% from Q2 to Q3 and 459% from Q1 to Q3.

Hackers are getting smarter, so companies and developers have to get smarter and more strategic about security practices. This is giving rise to the skyrocketing interest specifically around JSON Web Tokens and cloud security.

This quarter, we saw topic tags such as “JSON web token,” grow over 190% from Q2 to Q3, “cloud security issues,” grow about 10% from Q2 to Q3 and 434% from Q1 to Q3, and “web vulnerabilities,” grow by 18% from Q2 to Q3 and 459% from Q1 to Q3.

JSON Web Tokens (JWTs) are becoming more ubiquitous. Although they’ve been around for years, more organizations are complying with modern

security standards, particularly in Europe post-GDPR. For a better understanding of JWTs check out this article.

The growth in interest in cloud security relates to what Matt Quinn, COO at TIBCO calls the second major cloud migration. “There’s no cutting corners with this [cloud security]. If you don’t do the investments in the right place, in areas like CloudOps and DevOps, you don’t change your development practices.”

“People can still screw up,’’ Quinn adds. “But ultimately, security is something that we know what we have to do. Sometimes, we don’t do it. But I think everyone has a good idea and understanding of what good practices are. The early majority are probably still rediscovering some of those. And I think there are still some pockets of resistance to the cloud because of security-based issues.”

In other words, don’t cut corners and make sure you are adopting industry standards. Hackers aren’t slowing down, and neither should you.

Full Stack Developers, Frameworks and Popular Tutorials

The term “full stack” refers to both frontend and backend development. If someone is a “full-stack developer,” it means they have the skills and proficiency in both aspects of development.

This quarter, we saw growth in topic tags “full stack development”, which grew by over 97% from Q2 to Q3 and 547% from Q1 to Q3, “ tutorials”, which grew by about 85% from Q2 to Q3; 2395% Q1 to Q3, and “python frameworks” , which grew by 137% from Q2 to Q3 and about 950% from Q1 to Q3.

This quarter, we saw growth in topic tags “full stack development”, which grew by over 97% from Q2 to Q3 and 547% from Q1 to Q3, “ tutorials”, which grew by about 85% from Q2 to Q3; 2395% Q1 to Q3, and “python frameworks” , which grew by 137% from Q2 to Q3 and about 950% from Q1 to Q3.

ASP.NET is an open-source, cross-platform framework used for building web apps in C#. Many companies and developers are attracted to its user-friendly nature and are becoming overwhelmingly popular.

We talked with Microsoft MVP and tech leader, Gunnar Peipman (@gpeipman) about ASP.NET, why it’s so popular, and where he sees it moving into 2020. Peipman identified four key features about the language that made it stand out from other frameworks: its cross-platform abilities, lightweight and easy startup, abundant libraries, and high performance.

These features have led to increased interest in the framework that has led to more users.

“New users are coming from other ASP.NET [platforms] and so I think this transition will continue over the next few years. Many companies just cannot transition their current systems,” Peipman explains. Transitioning your codebase is no easy task. “So, I think over the next few years, ASP.NET development will be a hot topic.”

In addition to tutorials on ASP.NET, we also saw a huge jump in readership of tutorials on various Python frameworks. We spoke with Python developer and writer, Mike Driscoll, (@driscollis) about where Python for enterprise development is headed as 2019 comes to a close.

Driscoll highlighted why Python is popular amongst full-stack developers:

“The nice thing about Python web development is that it works on all PCs, across all platforms, so it’ll work on Windows, Mac, and Linux. And if you design it correctly, it’ll also work on most tablets and phones too. So, you’ve basically got a universal language, so to speak. That’s why it’s growing so much.”

Working Smarter, Not Harder

As 2019 draws to a close, developers want to make sure they have the right tools and processes in place to be successful through Q4.

One similarity between each of these topics and their related tags is tools. Developers want to find the best tools and frameworks to solve their problems — with as little startup time possible. Having the right tools for the job is critical, and that desire dominated Q3 readership results.

As we count down the final days of 2019, it will be interesting to see which trends carry over into 2020.

About the author:

Lindsay is a Content Coordinator at Devada. She works closely with contributors to DZone, a website for software developers and IT professionals to learn and share their knowledge. Editing and reviewing submissions to the site, she specializes in content related to Java, IoT, and software security.