20774 - Perform Cloud Data Science with Azure Machine Learning

Module 3: Managing Datasets

• Categorizing your data
• Importing data to Azure machine learning
• Exploring and transforming data in Azure machine learning

Lab : Managing Datasets

• Prepare Azure SQL database
• Import data
• Visualize data
• Summarize data

Module 4: Preparing Data for use with Azure Machine Learning

• Data pre-processing
• Handling incomplete datasets

Lab : Preparing data for use with Azure machine learning

• Explore some data using Power BI
• Clean the data

Module 5: Using Feature Engineering and Selection

• Using feature engineering
• Using feature selection

Lab : Using feature engineering and selection

• Prepare datasets
• Use Join to Merge data

Module 6: Building Azure Machine Learning Models

• Azure machine learning workflows
• Scoring and evaluating models
• Using regression algorithms
• Using neural networks

Lab : Building Azure machine learning models

• Using Azure machine learning studio modules for regression
• Create and run a neural-network based application

Module 7: Using Classification and Clustering with Azure machine learning models

• Using classification algorithms
• Clustering techniques
• Selecting algorithms

Lab : Using classification and clustering with Azure machine learning models

• Using Azure machine learning studio modules for classification.
• Add k-means section to an experiment
• Add PCA for anomaly detection.
• Evaluate the models

Module 8: Using R and Python with Azure Machine Learning

• Using R
• Using Python
• Incorporating R and Python into Machine Learning experiments

Lab : Using R and Python with Azure machine learning

• Exploring data using R
• Analyzing data using Python

Module 9: Initializing and Optimizing Machine Learning Models

• Using hyper-parameters
• Using multiple algorithms and models
• Scoring and evaluating Models

Lab : Initializing and optimizing machine learning models

• Using hyper-parameters

Module 10: Using Azure Machine Learning Models

• Deploying and publishing models
• Consuming Experiments

Lab : Using Azure machine learning models

• Deploy machine learning models
• Consume a published model

Module 11: Using Cognitive Services

• Cognitive services overview
• Processing language
• Processing images and video
• Recommending products

Lab : Using Cognitive Services

• Build a language application
• Build a face detection application
• Build a recommendation application

Module 12: Using Machine Learning with HDInsight

• Introduction to HDInsight
• HDInsight cluster types
• HDInsight and machine learning models

Lab : Machine Learning with HDInsight

• Provision an HDInsight cluster
• Use the HDInsight cluster with MapReduce and Spark

Module 13: Using R Services with Machine Learning

• R and R server overview
• Using R server with machine learning
• Using R with SQL Server

Lab : Using R services with machine learning

• Deploy DSVM
• Prepare a sample SQL Server database and configure SQL Server and R
• Use a remote R session
• Execute R scripts inside T-SQL statements