Oracle Autonomous Datawarehouse Cloud - Machine Learning with Oracle - Forecasting example скачать в хорошем качестве

Oracle Autonomous Datawarehouse Cloud - Machine Learning with Oracle - Forecasting example

Part 1 00:00 Welcome 00:26 Agenda 01:31 Example use case and problem statement 03:48 Data sources we will use 04:43 Machine learning theory - The "Naive" Model 05:28 Machine learning theory - Supervised Learning 08:00 Introduction to Autonomous Datawarehouse Cloud 09:24 Data collection - introduction 10:23 Data collection - DataSync demo Part 2 11:33 Create prediction model with ADWC - Introduction 12:28 Create prediction model with ADWC - Combine the sources 15:08 Create prediction model with ADWC - Feature engineering 16:46 Create prediction model with ADWC - Validation theory 18:48 Create prediction model with ADWC - Syntax to create the model 21:35 Create prediction model with ADWC - Actual validation, visual approach 24:02 Create prediction model with ADWC - Actual validation, numerical approach Part 3 26:08 Running the prediction model - A notebook to predict tomorrow's sales 27:07 Running the prediction model with ADWC - Automatically run it every day 27:22 Running the prediction model with ADWC - Embedding in an (APEX) application 29:05 Conclusions 31:23 How to get started 31:53 Questions and contact When it comes to forecasting accuracy, machine Learning often outperforms the traditional models such as ARIMA. In this video we show you step-by-step how to use the power of machine learning for forecasting sales/demand. This video is also a good way to learn how to work with machine learning in Autonomous Datawarehouse Cloud in general. The principles you learn here can be applied to many more machine learning use cases. We'll also cover any required ML theory, so you don't require any previous knowledge on this. After watching this video you will have the basic ingredients to apply ML to your own business cases with Autonomous Datawarehouse Cloud.