The advancement in AI and Machine learning has given a boost to every industry. You can consider the following open-source AI libraries for your business apps.
We have been publishing some really interesting and trending blog posts in the category of Artificial Intelligence. The most recent article demonstrated an introduction to AI, the types, and applications of Artificial Intelligence. However, this blog post is typically for software developers who are AI enthusiasts. There is a wide scope of development in this branch of computer science. In fact, the modern age absolutely belongs to Artificial intelligence. Just to recap, AI is the simulation of human intelligence in man-made machines. So, software organizations are massively investing in AI to enrich this technology with advanced features. Therefore, the open-source community has developed some enterprise-level frameworks and libraries to develop and deploy AI-powered business applications. Let’s start this guide and explore the top 5 open-source AI frameworks.
We will cover the following open-source AI libraries:
TensorFlow is an open-source framework for building Machine Learning(ML) algorithms to solve complex problems. It is one of the top open-source AI libraries that simplifies the development of Machine Learning models. In addition, TensorFlow offers a wide range of tools that help in preparing data sets, building ML models, and then deploying and implementing ML models. Further, this open-source Artificial Intelligence framework is cross-platform and you can build ML models for Desktops, Mobiles, and Web platforms.
Moreover, it offers an API for third-party integrations and comes with self-hosting capabilities. This free AI library is highly popular and is backed by a huge community. There are resources and documentation available for the developers and visitors. Above all, there are 171k stars and 87.7k forks on its GitHub.
PyTorch is another enterprise-level Machine Learning framework with a robust ecosystem. It comes up with a user-friendly front end, is easy to set up and you can install it locally or on the cloud. In addition, it is supported by Google Cloud Platform, Amazon Web Services, and Microsoft Azure. There is comprehensive documentation and resources available regarding development, testing, and deployment.
Moreover, PyTorch also offers neural network development which is an integral component of Machine Learning. This open-source ML framework is mainly written in C++ and Python and has very good stats on its GitHub with 62.1k stars and 17.3k forks.
Keras is a powerful open-source deep-learning API that offers rich Machine Learning tools to ease the developer’s burden. This ML platform runs on top of TensorFlow and offers simple workflows for fast experimentation. Above all, it is highly useful and is used by NASA, YouTube, and other popular giants. This open-source AI platform offers Machine Learning solutions to real-world problems more efficiently and quickly.
Scikit-Learn is another one of those open-source AI frameworks that are written in Python. It provides predictive data analysis and is highly scalable. This Machine Learning framework has been an integral part of AI systems of many big companies such as J.P.Morgan, Spotify, Booking.com, and more. Booking.com uses Sckikit-Learn to recommend hotels, and travel destinations to customers.
This open-source AI framework is also written in Python and very easy to set up as it requires fewer dependencies such as NumPy, SciPy, joblib and threadpoolctl. It also offers reusable components which are accessible to everyone. Further, there is a huge community and support behind Scikit-Learns, and also has good stats on GitHub with 52.7k stars and 23.9k forks.
Caffe is another open-source deep-learning framework that focuses on modularity and speed. It offers expressive architecture with high-level optimizations. This open-source Artificial Intelligence(AI) framework is extensible and robust for research industry deployment and experiments. Further, there is a vibrant community who have been active in code contributions.
The GitHub repo of the Caffe framework has encouraging stats with 33k stars and 19k forks. In addition, it is mainly written in C++ with a little input from other languages such as Python, and more.
This brings us to the end of this blog post. The key takeaways from this article are the top 5 open-source AI frameworks. In addition, we had a bird’s eye view of these open-source Artificial Intelligence frameworks. So, this guide will surely help you if you are seriously looking to equip your business software with Artificial intelligence. Undoubtedly, Machine Learning and Natural Language Processing are huge successes now and in the future. Moreover, there are very interesting and relevant articles that you may find out in the “See Also” section below.
Finally, containerize.com is continuously writing blog posts on further open-source products and topics. Moreover, you can follow us on our social media accounts Facebook, LinkedIn, and Twitter.
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Which framework is used for artificial intelligence?
TensorFlow is a very popular and enterprise-level open-source AI framework. Also, there arse some other options available such as PyTorch, Scikit-Learn and more.
Is TensorFlow open source?
Yes, it is open-source and comes up with self-hosting capabilities. Please visit this link to explore TensorFlow further.