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After the Azure free trial offer expires, as outlined in Option 1, these are the potential costs youcould incur as you continue to develop and consume these services.It’s always a good idea to be aware of the Azure Machine Learning pricing information in the eventyou hit on the next predictive analytics breakthrough for, say, predicting the next big stock market turn.Note that the preview Azure Machine Learning prices are subject to change at the time that theAzure Machine Learning services move into general availability (GA) mode.Create your first Azure Machine Learning workspaceLet’s create our first Azure Machine Learning workspace. At this point, you should be all set up witheither a free or paid Azure subscription or using the Azure Machine Learning free trial offer. Start bynavigating to the Azure Management Portal at https://manage.windowsazure.com. From there, clickthe left navigation bar for Machine Learning as shown in Figure 3-4.FIGURE 3-4 The Azure Machine Learning section of the Microsoft Azure Management Portal.44
An Azure Machine Learning workspace contains all of the tools you need to create, manage, andpublish machine learning experiments in the cloud. To create a new Azure Machine Learningworkspace, click the New icon in the bottom left of the page. Fill in the required fields as shown inFigure 3-5.FIGURE 3-5 Creating a new Azure Machine Learning workspace.The required inputs for creating a new Azure Machine Learning workspace include the following:Workspace Name Provide a unique name for your Azure Machine Learning workspace. Youwill know if it is unique by the presence of the green check mark to the right of the text box afteryou move the cursor from this field.Workspace Owner Provide a valid Microsoft account (formerly Windows Live ID). Note that itcannot be a non-Microsoft account, such as your corporate email account. To create a freeMicrosoft account, go to www.live.com.Location At the time of this writing, Azure Machine Learning services are available only in theSouth Central U.S. region.Storage Account Select the option to either create a new storage account or use an existingstorage account.45
Page 1 and 2: Azure MachineLearningMicrosoft Azur
Page 3 and 4: Hear aboutit first.Get the latest n
Page 5 and 6: PUBLISHED BYMicrosoft PressA divisi
Page 7 and 8: Supervised learning ...............
Page 9 and 10: KNN: K nearest neighbor algorithm .
Page 11 and 12: IntroductionMicrosoft Azure Machine
Page 13 and 14: Chapter 5, “Regression analytics,
Page 15 and 16: If you need additional support, ema
Page 17 and 18: Chapter 1Introduction to the scienc
Page 19 and 20: pack. By combining these deep psych
Page 21 and 22: Predictive analyticsPredictive anal
Page 23 and 24: Everyday examples of predictive ana
Page 25 and 26: 22 million: Average number of mail
Page 27 and 28: it began to learn at an exponential
Page 29 and 30: Chapter 2Getting started with Azure
Page 31 and 32: Data It’s all about the data. Her
Page 33 and 34: The concept of supervised learning
Page 35 and 36: to determine the model’s accuracy
Page 37 and 38: FIGURE 2-6 Testing the new predicti
Page 39 and 40: The web service then passes the inc
Page 41 and 42: Creating new prediction models usin
Page 43 and 44: Data center location Defines the ph
Page 45 and 46: This is a free Azure offer that is
Page 47: In terms of where you can host an A
Page 51 and 52: Machine Learning Workspace features
Page 53 and 54: Machine Learning Studio and then pu
Page 55 and 56: Number of instances in the dataset
Page 57 and 58: Create a new Azure Machine Learning
Page 59 and 60: experiment. Figure 3-13 shows the A
Page 61 and 62: FIGURE 3-16 Visualization of the Ad
Page 63 and 64: The workclass field is designated a
Page 65 and 66: Figure 3-20 displays a screenshot o
Page 67 and 68: FIGURE 3-22 Opening the column sele
Page 69 and 70: FIGURE 3-24 Training our new Azure
Page 71 and 72: FIGURE 3-26 Visualizing the results
Page 73 and 74: Evaluate the modelOne of the most c
Page 75 and 76: Receiver Operator Characteristic (R
Page 77 and 78: FIGURE 3-31 After the Prepare Web S
Page 79 and 80: If we click the toggle button again
Page 81 and 82: FIGURE 3-37 The Azure Machine Learn
Page 83 and 84: FIGURE 3-40 The Azure Machine Learn
Page 85 and 86: provide access to data over the Web
Page 87 and 88: Note that the sample Request Body d
Page 89 and 90: FIGURE 3-47 A sample Response Body
Page 91 and 92: Sample Code Here’s the best part:
Page 93 and 94: Testing the Azure Machine Learning
Page 95 and 96: FIGURE 3-53 Processing the Azure Ma
Page 97 and 98: ce-to-azure-marketplace/http://data
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The following is a listing of the a
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FIGURE 4-2 Select the specific impl
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FIGURE 4-5 Sample code for invoking
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FIGURE 4-7 Invoking the NuGet Packa
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FIGURE 4-9 Sample C# code to invoke
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Now watch what happens if we replac
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To do this, simply click the menu o
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FIGURE 4-16 Invoking the Azure Mach
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They fall short, however, in terms
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FIGURE 4-19 Selecting an Empty ASP.
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FIGURE 4-21 Selecting a Web Form it
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Validating the user inputTo further
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FIGURE 4-26 Invoking the Azure Mach
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Create a web service using ASP.NET
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FIGURE 4-29 Selecting the Visual St
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FIGURE 4-31 Adding a new item to th
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FIGURE 4-33 C# class data structure
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FIGURE 4-35 Adding the empty scaffo
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FIGURE 4-38 Installing the NuGet pa
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FIGURE 4-41 The IncomePredictionCon
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{Inputs = new Dictionary<string, St
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}incomePredResult.Sex = mlResultsAr
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FIGURE 4-44 A jQuery Mobile web app
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var iSex = document.getElementById(
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Chapter 5Regression analyticsIn the
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claims. It is easily seen how these
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Note that in this case, the Azure M
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FIGURE 5-4 The Upload A New Dataset
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FIGURE 5-7 Azure ML Studio: Selecti
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FIGURE 5-9 Selecting the option to
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FIGURE 5-12 The Clean Missing Data
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to .80. In this context, .80 means
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FIGURE 5-16 The automobile price pr
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FIGURE 5-18 The option to Visualize
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After clicking Publish Web Service
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FIGURE 5-23 The Azure ML Studio Reg
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SummaryIn this chapter, we took a d
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unsupervised machine learning, the
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Cluster analysis is not necessarily
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Milk Annual spending on milk produc
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Now that we have the Reader module
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After placing the Train Clustering
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he Metric parameter offers two opti
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the results of our K-means clusteri
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Train Clustering Model module remai
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Removes the Train Clustering Model,
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FIGURE 6-24 The wholesale customers
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FIGURE 6-26 The API help sample cod
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FIGURE 6-28 The CSV output file ope
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Chapter 7The Azure ML Matchboxrecom
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Back in the good old days of video
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webpages, recipes, or even other pe
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FIGURE 7-1 The restaurant ratings s
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FIGURE 7-2 Populating the three res
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Now it’s time to add the Train Ma
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Armed with this knowledge, let’s
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The last module to add to our Match
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prediction model will return a set
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FIGURE 7-17 The completed experimen
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FIGURE 7-19 The Azure Machine Learn
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Chapter 8Retraining Azure ML models
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Figure 8-2 illustrates the two appr
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Once you have re-created or located
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as a web service. After processing,
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After adding the three additional W
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FIGURE 8-9 Azure Machine Learning W
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FIGURE 8-11 A sample Azure Machine
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FIGURE 8-13 The two endpoints for t
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FIGURE 8-15 The Azure Machine Learn
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ResourcesFor more information about
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Free ebooksFrom technical overviews
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