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OML feature highlight: Time Series analysis with Oracle Machine Learning

Join us on this weekly Office Hours for Oracle Machine Learning on Autonomous Database, where Bhoopendra Singh, Implementation Specialist - DWH, Lake, Analytics, Data Science and AI will present the concepts about the Time Series algorithms available in Oracle Database, and will do a Live Demo on OML Notebooks. The Oracle Machine Learning product family supports data scientists, analysts, developers, and IT to achieve data science project goals faster while taking full advantage of the Oracle platform. The Oracle Machine Learning Notebooks offers an easy-to-use, interactive, multi-user, collaborative interface based on Apache Zeppelin notebook technology, and support SQL, PL/SQL, Python and Markdown interpreters. It is available on all Autonomous Database versions and Tiers, including the always-free editions. OML includes AutoML, which provides automated machine learning algorithm features for algorithm selection, feature selection and model tuning, in addition to a specialized AutoML UI exclusive to the Autonomous Database. OML Services is also included in Autonomous Database, where you can deploy and manage native in-database OML models as well as ONNX ML models (for classification and regression) built using third-party engines, and can also invoke cognitive text analytics. 00:50 Topics for today 01:08 Upcoming Sessions 02:06 Time Series Forecasting 02:48 Time Series in OML 05:28 Time Series Patterns 08:52 Exponential Smoothing 10:40 Simple Exponential Smoothing 11:31 Models with Trend but no Seasonality 12:46 Models with Seasonality but no Trend 13:52 Models with Trend and Seasonality 14:45 Demo: Forecasting Sales using Exponential Smoothing for Time Series 30:21 Q&A

Resources

Workshop Info

Session Has Completed - 12 October 2021
1 Hour
Oracle Machine Learning Office Hours
English
Oracle Machine Learning