Getting started with Data Science in Microsoft Fabric

Looking to get started with Data Science in Microsoft Fabric? In this session, we'll walk through how to get started by creating a Jupyter notebook, download sample data from our lab, create a ML forecast with Prophet, and cross-validate and evaluate the model. We'll then store the model in MLflow and see how to use it both in the notebook and in the Fabric workspace. The notebook is available for download in the data science module in our lab at https://aka.ms/fabricrealtimelab -- this module is designed to be stand-alone, so it can be completed without finishing other modules in the lab. Links from video: Real-time Lab with Notebook https://aka.ms/fabricrealtimelab Prophet https://facebook.github.io/prophet/ Chapters: 00:00:00 Introduction 00:00:46 Eventstream ingestion to Lakehouse 00:01:24 Overview of the Jupyter Notebook 00:03:18 Download historical data 00:03:55 Load CSV into dataframe and process 00:07:35 Quick look at Data Wangler 00:09:14 Training the model (Prophet) 00:16:15 Cross-validation 00:24:12 Log the model with MLflow 00:25:28 Loading the model and generating predictions 00:29:52 Comparing the model vs actual 00:31:27 Scikit-learn metrics 00:32:29 Additional MLflow 00:33:02 Looking at the models in the UI