Description
Today’s data scientists and machine learning engineers now have a wide range of choices for how they build models to address the various patterns of AI for their particular needs.
Summary
- Over the past two decades, the biggest evolution of Artificial Intelligence has been the maturation of deep learning as an approach for machine learning, the expansion of big data and the knowledge of how to effectively manage big data systems, and affordable and accessible compute power that can handle some of the most challenging machine learning model development.
- These toolkits are in turn embedded in many larger machine learning platforms including those mentioned below.
- Data science notebooks offer the full breadth of machine learning algorithms through support and embedding of many of the popular machine learning toolkits mentioned above.