Cloud Workshop - Machine Learning
Lab
Advanced
3 h 15 m
2019-10-05
Lab Overview
In this hands-on lab, you will use Azure Databricks in combination with Azure Machine Learning service to build, train and deploy desired models. You will learn how to train a forecasting model against time-series data, without any code, by using automated machine learning, and how to score data in real-time using Spark Structure Streaming within Azure Databricks. You will create a recurrent neural network (RNN) model using PyTorch in Azure Databricks that can be used to forecast against time-series data and train a Natural Language Processing (NLP) text classification model using Keras.At the end of this lab, you will be better able to build solutions leveraging the Azure Machine Learning service and Azure Databricks.

Related Learning Path(s):
Machine and Deep Learning - ILT
DP-100: Designing and Implementing an Azure Data Science Solution on Azure
Objectives
  • Understand the features of Azure Machine Learning Services
  • Understand how Azure Machine Learning may be used with Azure Databricks
Exercises
In this exercise, you will deploy and configure the Azure Databricks cluster and the Azure Machine Learning Workspace.
In this exercise, you will create a model that predicts battery failure from time-series data using the visual interface to automated machine learning in an Azure Machine Learning workspace.
In this exercise, you will create a deep learning model for time series data in Azure Databricks and leverage Azure Machine Learning services to register the model.
In this exercise, you will apply the forecast model to a Spark streaming job in order to make predictions against streaming data.
In this exercise, you create a model for classifying component text as compliant or non-compliant.
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