Article

The Best Development Libraries For AI and Machine Learning

The-Best-Development-Libraries-For-AI-and-Machine-Learning-scaled

An AI development library is similar to any other development library. Development libraries are not themselves programs, but they contain many of the tools (segments of code, functions, etc.) used to build specific types of programs.

For example, a development library for an online shop might contain things like code for shopping carts, product pages, and discounts.

AI libraries essentially offer the same thing, though often in less concrete terms, as AI systems are much more complex than an online shop. This is the reason why AI development libraries are so important and widely used — AI is such a complicated field that development libraries are required for just about everyone looking to start in AI.

What’s great about libraries is that it’s made AI, one of the most complicated areas in computer science, accessible to a much broader audience. To help you find the library that’s right for you, we’ve curated five of the most popular AI development libraries currently available for free.

The Best AI Development Libraries

For Everyone: TensorFlow (Google)

Language: C++ or Python

TensorFlow is a free and open-source software created by Google and used by developers to experiment with AI and neural networks. Various branches of Google use TensorFlow as the foundation for their projects, and it’s one of the most popular tools used by commercial and research AI development teams. The software is designed to do most of the heavy lifting of experimenting with neural networks, making it quicker and less daunting for programmers to dive into the field.

For Beginners: Keras (Google)

Language: Python

Keras is another open-source project created by Google that runs on top of TensorFlow and a few other libraries. The goal of Keras is to make neural networks more accessible and simpler for general developers. The project is written in Python, one of the easiest and most popular programming languages to learn. This has made it an excellent tool for programmers of all skill levels who want to start experimenting with AI.

For Python Users: PyTorch (Facebook)

Language: Python

PyTorch is Facebook’s offering to the pool of open-source neural network toolkits. Unlike TensorFlow, which was adapted to work with Python in the Keras release, PyTorch was designed from the start to work with the Python programming language. This allows PyTorch to offer a more seamless programming experience with abilities like Python debugging through pdb. While TensorFlow dominates research and commercial AI development, PyTorch adoption has been growing rapidly.

For Robotics: Isaac (NVIDIA)

Language: C

The Isaac platform by NVIDIA is a software developer kit used to help train AI, specifically AI used in robotics. Like the other AI frameworks mentioned in this post, it has resources that make it easier and faster to get a neural network off the ground. Where it differs from its peers, though, is in its testing and training features. It’s made with the very specific intention to take existing robotics to the next level by challenging robots, helping them learn, and providing them with the tools to solve problems more effectively.

For Researchers: OpenAI Gym

Language: Python

Based in San Francisco, OpenAI is a nonprofit, open-source research company dedicated to exploring the possibilities of AI. Its goal, which has found support from tech titans like Elon Musk, is to push AI as far forward as possible in the hopes that they (or someone using their open-source resources) will achieve safe and beneficial artificial general intelligence— an AI that can think and learn at the same level as humans.

Despite only being founded in 2015, the small team has already used its project to defeat the best Dota 2 e-sports team in the world. They have also created a text generation feature with the AI so powerful that the team pulled it from their open-source software, feeling that it was too dangerous for the general public.

Starting A Journey In AI Development

Finding the right library for your AI project is important, but don’t let it get in the way of starting your AI journey. Remember that all of these libraries are free to use and that you can switch between them as you need. If you’re not sure where to start even after going through this list, TensorFlow is probably your best bet as it has the most support and information online. Our white paper on AI Software & Hardware Options discusses the many resources available today for starting an AI project.

AI-Software-and-Hardware-Options
Steve-Hulet-Default-BW_optimize.jpg

Steve Hulet

CTO

Steve is the Co-Founder and CTO at Fresh. A former Software Engineer at Amazon with over 12 years of web development experience, Steve provides technical, architectural, and engineering oversight to projects. Steve is responsible for all technology reviews related to websites. His specialities include programming languages such as C, C++, Java, Python, and PHP, and technology software including Eclipse, GLPK, jQuery, Linux, and MATLAB. Steve’s skills include automation, databases, linear programming, optimization, and testing, all of which he uses in conjunction with Fresh’s digital strategists provide innovative solutions to clients.