Introduzione

In this whiteboard design session, you will work with a group to design and implement a solution that combines Azure Databricks with Azure Machine Learning service to build, train and deploy the machine learning and deep learning models. You will learn how to use automated machine learning, model lifecycle management from training to deployment, in batch and real-time inferencing scenarios, and construct deep learning models for Natural Language Processing (NLP) in text classification and forecasting against time-series data. Finally, you’ll learn to compare data with PyTorch and Keras for deep learning.

This workshop is intended for Cloud Architects and IT professionals who have architectural expertise of infrastructure and solutions design in cloud technologies and want to learn more about Azure and Azure services as described in the ‘About this Course’ and ‘At Course Completion’ areas. Those attending this workshop should also be experienced in other non-Microsoft cloud technologies, meet the course prerequisites, and want to cross-train on Azure.

Obiettivi del corso

After completing this course, students will understand the capabilities and implementation solutions of Azure Machine Learning and Azure Databricks.

Struttura del Corso

MODULE 1: Whiteboard Design Session - Machine Learning

Lessons

Review the customer case study

Design a proof of concept solution

Present the solution

MODULE 2: Hands-on lab - Machine Learning

Lessons

Creating a forecast model using automated machine learning

Understanding the automated ML generated forecast model using model explainability

Creating a deep learning model (RNN) for time series data and registering the model

Using a forecast model for scoring of streaming telemetry

Creating a deep learning text classification model