ML.NET vs. Oracle Data Science vs. PredictSense vs. SQL Server Comparison Chart

A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results.

Intelligence and security are built into Microsoft SQL Server 2019. You get extras without extra cost, along with best-in-class performance and flexibility for your on-premises needs. Take advantage of the efficiency and agility of the cloud by easily migrating to the cloud without changing code. Unlock insights and make predictions faster with Azure. Develop using the technology of your choice, including open source, backed by Microsoft's innovations. Easily integrate data into your apps and use a rich set of cognitive services to build human-like intelligence across any scale of data. AI is native to the data platform—you can unlock insights faster from all your data, on-premises and in the cloud. Combine your unique enterprise data and the world's data to build an intelligence-driven organization. Work with a flexible data platform that gives you a consistent experience across platforms and gets your innovations to market faster—you can build your apps and then deploy anywhere.