Python For ML And AI: The Factors That Make Python Best For High-End Projects

The pace of business progress and being driven by technological advancements has whooshed over recent years. However, choosing the “right tool for the right task” is still grueling for many enterprises because there is a wide range of technologies and elements to give thought to from a business perspective. Enhancing business scalability and improving operations in a fruitful manner is what every organization, irrespective of the industry, aims to achieve. While organizations are geared towards uplifting the business environment profoundly, making a decision to choose innovative business tools, and assets to measure and interpret the processing of the data and information within a business is another task to contemplate. 

When the discussion about online solutions sees the light of day, the most obvious thing that businesses can count on is “the programming language” that can transform the business downright. In this particular article, Python – the high-level programming language takes center stage in which finding whether Python for ML and AI federated projects is really worthwhile or it is just a hoax-tune everyone is humming would unquestionably be appealing. 

Machine learning and Artificial Intelligence are technologies that will be having a major impact on industries in the coming years. There are impressive varieties of programming languages available to software developers today. It is not just the popularity to brood over but the functionalities that need to be analyzed before choosing the right language to assimilate the project with. 

When it comes to ideating over a particular thing, the objective needs to be examined thoroughly. Here in this case, when you have to decide on the right programming language, you will definitely have to consider how scalable, technical, and complex the project is, and moreover, what you are trying to accomplish possibly with Python?

This blog post about Python for machine learning and AI-assimilated software development will walk the readers through the most decisive factors of how this specific programming language can be beneficial for a project that is built over AI and ML technologies.

Difference Between Artificial Intelligence and Machine Learning

Do you know that the number of businesses adopting AI surged by 270 percent in just four years? Also, one of McKinsey’s surveys reveals that around 20% of the C-Suite is using machine learning. The recognitions just do not stop here. AI and ML have enormous benefits to surprise the people with. The world is now overwhelmed with the technologies and intelligent machines that are ultimately driving businesses to all intents and purposes. AI is a much bigger concept that is known to stimulate human thinking and behavior and emulates the same into processing while machine learning is a subset of artificial intelligence which enables smart machines to perform a particular task and give an accurate result. 

The major difference between AI and ML is the range of scope. Artificial intelligence has a vast array of scope and can be integrated with different machines altogether but machine learning (read about – Beginners Guide to Machine Learning) has a limited scope. Now, this particular statement could let you think deeply about how Python for machine learning and artificial intelligence will bring forth the oceans of opportunities for businesses. Smart assistants, social media monitoring using tools, chatbots, and healthcare management tools are common examples of AI. Image and speech recognition, video surveillance, product recommendation are some great examples of machine learning.

Thinking of Using Python for ML and AI Software Projects? Know a Bit More About Python First.

Python is an object-oriented programming language that is majorly used for web-development and system scripting by developers and programmers. Python works on different platforms and connects files and codes to database systems that can also be modified according to the requirements. Python is not a newly-discovered programming language as it has been in the industry for a longer period now. Its nature of being concise and easy with codes makes it the leading choice for deploying projects integrated with AI and ML. 

Also, Python is emerging to be the most popular programming language among developers in the field of machine learning which is a plus point. Since you now have a brief of the Python capabilities and how they can bring the best out of developers, looking through some unexplored aspects of Python being supremely efficient for AI and ML development could be a smart choice. Now the crux of the matter is – what could possibly lead you to deploy Python for ML and AI-integrated software projects? Outwardly, the characteristics. Here are some apparent features of python in AI and ML.

• Easy to code and scalable.
• Free and open-source.
• Highly portable and integrated by nature.
• Supports GUI.
• Wide range of libraries that proliferate development cycles.

Seven Notable Factors That Make Python the Best Programming Language for Machine Learning and AI?

The market is seemingly picking up steam to churn out newly discovered programming languages making developers experience the programming efficiency with various functionalities. To those who are new to the field of machine learning and programming language, deploying the right language to code the program might appear daunting unless you know the project’s problems and challenges. 

If being a developer or an enterprise you are asking yourself a question – how secure and reliable Python for ML and AI is? Or maybe it is really the best programming language to use for my project that requires the integration of AI or ML or both. Let’s dig into the extensive highlights Python has to offer to know this state-of-the-art language. 

Offers Concise and Readable Code

Why do developers choose to code via expressive programming languages? The implementation of easily integrated languages rich with integral language concepts enables programmers to maintain codes that are easy to integrate and read. The popularity of Python is no alien to developers and business enthusiasts. In fact, its syntactical constructions are eulogized highly by the programming community. The concise syntax and manageable structure of the Python programming language make it worth combining with AI and ML projects. The growth of the artificial industry in retail industry and many prominent sectors is unprecedented. This is why a Python app development company consolidates models for software development for AI and ML. Even though Python is touted as one of the high-level programming languages, it is still billed as a developer-friendly language that requires no technical stirring up from the developers’ side.

Provides an Extensive Library Environment

The most preferred language for a programmer is the one that appears most comfortable and renders ease of use. Python is one of the most popular programming languages owing to a vast range of libraries for machine learning, web development, scripting, etc. Hence, if you are thinking of employing Python for ML and AI without messing up with the codes, you are not mistaken. The developers of the 21st century have a variety of options to tap into in terms of programming languages. However, Python still tops the list of trending and top programming languages. A leading news website reveals that around 8.2 million developers in the world use Python for development projects. The best thing about Python Collection of build classes is developers are not required to program the code from scratch for new functionality as that earlier saved library will likely serve the best.

Has a Widespread Developer Community

Machine learning and AI are proving to be boons for the IT industry. Since machine learning is a part of artificial intelligence, the perception of both technologies is different, which in broader waves, brings the concept of logical machines and gives a veracious vision to products and solutions. Why is Python used for machine learning and artificial intelligence-rich project development? It is anticipated that over 60% of machine learning developers are prioritizing Python for development as it continues to dominate other programming languages and proliferates in solving trivial queries with the help of an informed community. The Python developer community is one of the most rigorously active language communities that never fails at providing conducive developer support.

Versatile, Dynamic, and Reliable

Since web and mobile app development continue to rise at a swift pace, selecting a programming language that could be a perfect fit for your web-development project encompasses various aspects. Everything apart, versatility and reliability are the two most important factors that can lead the developers to make up the mind regarding what could be the best choice from the AI point of view for website design and development. Moreover, providing a great user experience can only be approached via unique ideation behind the digital medium. So if you are still pondering what makes Python for ML and AI reliable and efficient, it is the portability rate. The development and portability rate in Python are very high, which allows the applications to embrace the technological element easily.

Integrate Well With Machine Learning and AI

Python is assimilated with the most popular features used by data scientists such as compatibility with statistical analysis, open-source, best fit for exploratory tasks, etc. It has been observed that Python is broadly preferred among programmers in IT businesses who are looking for a general-purpose language that can amalgamate well with new-age technologies such as AI and ML. Python for machine learning projects is supported well by the deep learning libraries and a large community of programmers who have a thorough understanding of the text processing tools. No wonder AI and ML are the hot topics that are endeavoring to break the technical barriers and Python for ML and AI proving to be extremely successful in letting them achieve what they want.

Supports Testing Automation

Selecting the right programming language for test case automation is like grasping at straws – one of the arduous choices. It is because a wrong selection can eventually lead everything to go dud. Since Python is easy to code, and read and moreover contains less verbosity, the majority of developers depict their trust in Python for projects that have high-end characteristics to look after. If we talk about the test automation advantages of Python in machine learning and AI, it is beyond the moon and back. The flexibility of the language and its boastful nature as the most comprehensive frameworks that work in favor of ML is cemented as a highly portable language with multiple capabilities.

Best for Complex Algorithm Implementation

Algorithms are one of the most important things in regard to the development of AI and ML integrated software. However, the elements such as training data set, supervised process, and bringing practical value into being are some of the widely considered aspects that developers should ponder over before selecting Python for ML and AI implementation. The systems, technicalities, and functions of AI development solutions are much more complex than any other project. Therefore, it is more than important to deploy the best programming language for machine learning and projects that have anything to do with intelligent features.

7 Astonishing Facts About Python Every Developer Should Know

• The users belonging to the age of 21 to 29 use Python most.
• The creator of Python, Guido van Rossum, was a big fan of the TV show and he named the language after a TV program and that’s how this innovative programming language got its name – Python.
• According to Statista reports, Python is the fourth most-used programming language in the globe with 44.1% of likes.
• In one of the surveys conducted by Github of most-searched programming languages in Google, Python took first place with 29.9 % surpassing Java and JavaScript.
• Bigwig companies like Google, IBM, Netflix, Facebook, Reddit, Spotify, Udemy, etc. use Python for web development.
• Python is the only programming language that does not use braces to delimit code usage.
• Python remains the preferred programming language by Information Technology professionals to upskill in India in 2020.

Though Python use cases for AI and ML are enough to reel the developers in for AI and ML blended projects, is Python the only best programming language for web app development that can uplift the AI and ML integrated software programs? Since AI and ML programming are intricate and powerful, there are many factors that contribute to the efficiency of making the software as worthwhile as possible and therefore the programming language selection is the meat of the matter. Let’s have a look at some Python alternatives for AI and ML software projects.

Five Python Alternatives for AI and ML Software Development

Choosing Python for ML and AI development has many advantages but there probably are some disadvantages that could be a roadblock in combining AI programming languages with tools. Hence, we should always be ready with the backup plan, which means considering other programming languages as well.

• Java: When one thing of the Python alternative, Java is the name that will certainly be on the list as this language is as appealing as Python. Java uses virtual machine technology that comes as a plus point for all the developers who are working upon a software development that has some characteristics of AI and ML. (Read – Java vs Python: The Fierce Battle of the Beasts).

• NodeJS: Commonly known as Javascript runtime, NodeJS could be one of the best choices for AI integrated projects if you are looking forward to cutting down on the development time with minimalistic features. Javascript provides an interactive loop and works as similar as Python for ML and AI or even better in some instances. While Python has a library advantage, NodeJS is capable of GPU-level performance.

• R: R is a statistical-computing and graphics-oriented programming language that compiles different platforms. R is one of the most preferred programming languages that alleviate specific tasks diligently. Its open-source nature makes it the perfect choice for AI-integrated software projects. Moreover, some of R’s features such as cross-platform support, a large standard library that is equally good as Python, and an extremely compatible nature would make you think why Python for machine learning projects and not R.

• Lisp: One of the oldest and widely used programming languages, Lisp enables developers to overlook many features of Python in AI and ML and garner traction. Lisp is one of the programming languages that acts as an integral language for AI programming and a functional tool for machine learning. Lisp might be having limited libraries but even without it, there are things that it uses to manifest and deploy into AI programs.

• Scala: Scala is much similar to Java and Python in syntax and algorithms. The majority of people go by opting Python for ML and AI is because they might have not explored the other languages so far. The speed and efficiency of accomplishing a project are what make it stand out to use it for AI and ML integrated models. Hence, if you are trying to discover a potential programming language that can beat Python, Scala is simply the most considerable choice that can be made by developers.

Final Words

If you are hesitant in comprehending if Python would be able to shape your new AI-mainstreamed project, get in touch with our tech-experts to discuss the requirement and they will help you make an informed decision.