As we race toward a digitized, hyperconnected, and automated future, the demand for products and services that can support those needs grows. Enter the data science (DS) and machine learning (ML) markets—both dedicated to understanding the science of what patterns and algorithms can offer enterprises for the future of their businesses. For AI use cases to work in the real world, organizations need data science and machine learning platforms to build, maintain, and continuously improve models’ accuracy and relevance.In this report, we focus on comparable views and analysis of the strengths of data science and machine learning platforms.
The 2020 HFS Top 10 Data Science and Machine Learning Platforms report examines key players in this evolving industry. We assessed and rated the capabilities of 14 data science and machine learning platform vendors as viewed in practice across a defined series of innovation, execution, and voice of the customer criteria. This report highlights the overall ratings for the 14 platforms and the top leaders for each sub-category.
This report also includes detailed profiles of each vendor, outlining their overall and sub-category rankings, provider facts, and detailed strengths and weaknesses. The report focuses on data science and machine learning according to voice of the customer (VoC) feedback and competence in two main categories. Execution: the ability to do predictive analytics and machine learning inferencing, model visualization, and the overall ease of consumption and maintenance for enterprise customers Innovation: the overall technology innovation, scalability and flexibility, and investment in user interface (UI) and user experience (UX).
Platform providers covered include:
AWS SageMaker Databricks Unified Analytics Platform Dataiku DataRobot Domino Data Science Platform Google H2O.ai IBM Watson Studio/Watson ML KNIME Analytics Platform Microsoft Azure Machine Learning Studio RapidMiner SAP Analytics Cloud SAS TIBCO
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