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Guide: Open-Source Tools and Libraries for Enterprise Data Science and Machine Learning
Open-source collaboration has led to some of the most innovative and advanced technologies of our time. These are data science and machine learning tools and libraries that equip data scientists in every industry, including engineering, manufacturing, cybersecurity, medicine, genetics, and astronomy.
Open-source technologies empower organizations to do breakthrough data science and create differentiating AI and machine learning technologies. Python is the most commonly used and most recommended language for data science and machine learning, which is why many of the open-source tools and libraries are built for Python. It is also growing in popularity among developers — it is currently the second most popular language on GitHub. As Python becomes a common language between developers and data scientists, getting machine learning models and applications through production becomes more efficient. All of the tools listed in this guide are compatible with Python.
There are thousands of open-source data science and machine learning packages. This guide focuses on a common set of tools that cover most fundamental tasks in the realm of data science and machine learning. It also touches on a few tools to take ML and data science to the next level as well as cutting-edge tools that are at the forefront of solving are the next great challenges in AI.
View the guide below or download the PDF.
