Working in Machine Learning and Artificial Intelligence? Here’s Top Reasons to Use Python
Who would’ve thought that machines will fix appointments, suggest songs, and decide the best route…basically add ease and efficiency in our lives. You guessed it correct, machine learning and artificial intelligence is what will drive the present towards a more efficient and user friendly future. These technologies enhance search functionality, personalization, and provide smart recommendations. User experience has been redefined and now creates immense value across industries.
Why use Python when bringing the above-mentioned experiences to life. Let us take a look at some of the top reasons for doing so.
Why Is Python the Preferred Choice in AI & ML?
The tech stack for ML & AI varies a lot and is different when compared to traditional software development projects. There is a need to carry out deep research and the right set of skills. The programming language that you use should have the necessary tools, and be stable, and flexible at the same time. Python offers the programmers a required set of tools that help them from development to deployment and then the maintenance. Other such benefits that make Python a preferred choice in ML & AI are consistency, simplicity, flexibility, access to libraries and frameworks for AI and ML, and a big community.
1. Easy to Use
Programmers work with complex tools, but believe us…no one prefers things to be complicated. Python offers an easily readable syntax and this makes it a preferred choice for experimental students and experienced developers at the same time. Rather than spending their time and resources to understand the technical jargon and nuances, the developers can now focus on the problem at hand and effectively solve it. Efficiency in Python helps developers write fewer lines of code while completing more work at the same time. Developers can easily understand the python code and this makes it easier for them to further craft efficient machine learning models.
2. Multiple Libraries and Frameworks
In the last 30 years, Python has proved to be a great tool in the hands of developers. There have been many changes, additions, and upgrades overtime. Now there are hundreds of libraries and frameworks that the developers can use. These wide ranges of libraries and frameworks help developers to save a lot of time and energy when working on ML & AI projects.
Some of the libraries that are specifically beneficial in the machine learning and artificial intelligence environment are TensorFlow, Keras, and Scikit-Learn. The best part is that these three libraries are open source and developers can experiment these with other networks as well.
3. Not Platform Dependent
In programming terms platform independence is a feature in a framework that allows developers to implement changes on one machine and then use them on a different machine without or minimal changes. Python is a platform independent language and is supported by several platforms such as Mac, Linux, and Windows. So there is no need to use an interpreter when working with python language as it can be used to create standalone executable programs that can be used on different platforms with ease. Developers use Amazon or Google for their computing needs, and there are still many programmers who use their own powerful machines with heavy GPUs when training their machine learning models. As python is not dependent on any platform, it helps in the training being cheaper and much easier.
4. Great Community
Python is among the top 10 programming languages in the world. This also means that apart from ease of programming, the developers can easily find the help and support they are looking for when working in this framework. When building your AI based project, you can easily find the appropriate framework to support you. In the last 30 years, many have learned and are learning python programming, and so it is also easier for companies to find developers or development companies when there is a huge project. There are several forums, and a great contributing online community that keeps adding new and informative material on machine learning. This furtherance of technical know-how helps in creating more innovative and efficient solutions.
5. Cost Effective
This is one of the most important aspects that businesses look for in development projects. Having a cost effective solution is all the more crucial in machine learning and artificial intelligence projects. These projects cost a lot, and so enterprises need to carefully look at the aspects that can cut the cost in the long run. Python is cost effective because it is stocked up with advanced features, community, and customizable solutions to help in ML & AI. Developers can create the right solutions for enterprises. Having a cost effective solution helps businesses in implementing new and interesting products in the market. This is yet another reason why most developers and client companies prefer to carry out their development in this programming language.
The above-mentioned reasons highlight the reasons why Python is a preferred programming language. However, several other aspects add to its value when being used for machine learning or artificial intelligence projects. If you are looking for Python development in your next project, why not get in touch with the professionals to know more.
Continuous Support in Machine Learning and Artificial Intelligence
Machine learning and artificial intelligence as we know are the technologies that will reshape our future. With time there have been many new innovations and features that have been added in the industries across the world. While the world awaits its perfect solution, there will be several new ones that will lead up to that perfect solution. However, in the meantime, the constant support in the programming is what will help developers focus on creating the right solution. Python has proved its mettle in supporting the ML and AI technologies, and will keep on adding new features to empower developers to achieve even more complex results with ease. So why not rely on this programming language for your next ML or AI projects?
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At Codetru, we work with several frameworks, programming languages, and we have extensively used python to create appropriate solutions for our clients. Especially when working with machine learning and artificial intelligence projects, we have experienced the best results. It is not just the ease of programming but also the wide range of possibilities that help add new dimensions and take the project to a completely new level. We have an excellent team of python programmers who have hands on experience on crafting state of the art solutions in ML and AI, and we wish to extend our teams support to empower you as well. Get in touch with us to know more about how we can collaborate and create the best solution using python.
FAQs about using Python for AI and Machine Learning
1. Why Python is preferred for AI and Machine Learning?
AI and Machine Learning prefer Python for its simplicity, readability and ease of use. Developers can write and understand Python code faster, allowing them to focus on solving complex problems rather than dealing with syntax. This makes it an ideal choice for beginners and experienced programmers developing AI and ML projects.
2. What makes Python cost effective for AI and ML projects?
Python is cost-effective for AI and ML projects due to its extensive libraries and frameworks, which are often open source. This reduces the need to build tools from scratch, saving time and money. Additionally, Python’s large community ensures continued support and updates, further reducing development costs.
3. How does Python’s platform independence benefit AI and ML development?
Python’s platform independence allows developers to implement and run their code on a variety of operating systems, including Windows, Mac, and Linux, without significant changes. This flexibility makes it easier to develop, test and deploy AI and ML models across platforms, streamlining the development process.
4. What are the popular Python libraries for AI and ML?
Some popular Python libraries for AI and ML are TensorFlow, Keras, and Scikit-Learn. This library also provides pre-built modules and functions that simplify the development of machine-learning models, enabling developers to build complex AI applications and use them efficiently.
5. How does community support for Python enhance AI and ML projects?
Python’s extensive and dynamic community support advances AI and ML projects, providing a wealth of resources including tutorials, seminars and documentation. This community-driven support ensures that developers can easily find solutions to problems, share knowledge, and keep up with the latest advancements in AI and ML technologies.
