collab365 empower-your-applications-with-azure-machine-learning
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Online Conference
June 17th and 18th 2015
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Empower Your Applications with Azure Machine Learning
David WalkerTech Aspect
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David WalkerTech Aspect
Email : [email protected] : @DavidWalkerFacebook : LinkedIn :
Sitecore Practice Directory, Sitecore MVPOver 20+ years exp, 75% as a ConsultantCertified Scrum Master, Scrum DeveloperMCP in 2003, MCAD & MCSD in 2005Former Senior App Dev at Microsoft Former two-time Microsoft ASP.NET MVP
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AgendaWhat is Azure? This is Collab365 - You got this!What is Machine Learning?What is AzureML?DataMarket.AzureApplication IntegrationAPI/Data Management
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POP QUIZ: What is Machine Learning?
“Field of study that gives computers the ability to learn without being explicitly programmed”.Arthur Samuel – 1959, source Wikipedia
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Machine Learning / Predictive Analytics
Vision Analytics
Recommenda-tion engines
Advertising analysis
Weather forecasting for business planning
Social network analysis
Legal discovery and document archiving
Pricing analysisFraud detection
Churn analysis
Equipment monitoring
Location-based tracking and services
Personalized Insurance
Machine learning & predictive analytics are core capabilities that are needed throughout your business
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Machine Learning Overview• Formal definition: “A computer program is said to learn from
experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E” - Tom M. Mitchell
• Another definition: “The goal of machine learning is to program computers to use example data or past experience to solve a given problem.” – Introduction to Machine Learning, 2nd Edition, MIT Press
• ML often involves two primary techniques: – Supervised Learning: Finding the mapping between inputs and outputs using
correct values to “train” a model– Unsupervised Learning: Finding patterns in the input data (similar to Density
Estimates in Statistics)
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Machine LearningData: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
Rules, or Algorithms:about, Learning, language – Spelling and sounding builds wordsLearning about language. – Words build sentences
Learning, or Abstraction:Any new understanding proceeds from previous knowledge.
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Supervised Learning1. Used when you want to predict unknown answers from answers you already
have – requires data which shows the answers you can get now2. Data is divided into two parts: the data you will use to “teach” the system
(data set), and the data you will use to see if the computer’s algorithms are accurate (test set)
3. After you select and clean the data, you select data points that show the right relationships in the data. The answers are “labels”, the categories/columns/attributes are “features” and the values are…values.
4. Then you select an algorithm to compute the outcome. (Often you choose more than one)
5. You run the program on the data set, and check to see if you got the right answer from the test set.
6. Once you perform the experiment, you select the best model. This is the final output – the model is then used against more data to get the answers you need
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Unsupervised Learning1. Used when you want to find unknown answers – mostly groupings -
directly from data2. No simple way to evaluate accuracy of what you learn3. Evaluates more vectors, groups into sets or classifications4. Start with the data5. Apply algorithm6. Evaluate groups
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Unsupervised Learning• Example 1 example A Example 2
example B Example 3 example C
example A example B example CExample 1 Example 2 Example 3
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AgendaWhat is Azure? This is Collab365 - You got this!What is Machine Learning?What is AzureML?Market PlaceApplication IntegrationAPI/Data Management
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Why is AzureML so Awesome?• Google was first with just a simple Prediction Service, but it
required a lot of thought/work in building appropriate data sets
• AzureML is less restrictive on data sets and with a much friendlier set of tools has made it so that anyone can do it – no PhD required.
• Then, easily integrate it into your applications, processes – even Excel.
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How can you use AzureML today?• Search DataMarket.Azure.com for published
services/experiments• Text Analytics – Sentiment• Twitter Sentiment Analysis• Lexicon Based Sentiment Analysis
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Create your own AzureML experiments?• Set up a Microsoft Azure Account• Set up a Storage Account• Load Data• Set up an AzureML Workspace• Accessing AzureML Studio• AzureML Studio Tour
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0 – The bar was closed before they determined the most efficient door to enter.
10 Data Scientist standing outside a bar, how many enter?
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AgendaWhat is Azure? This is Collab365 - You got this!What is Machine Learning?What is AzureML?DataMarket.AzureApplication IntegrationAPI/Data Management
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AgendaWhat is Azure? This is Collab365 - You got this!What is Machine Learning?What is AzureML?DataMarket.AzureApplication IntegrationAPI/Data Management
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Application Integration• Calling AzureML end points
• http://microsoftazuremachinelearning.azurewebsites.net/ClusterModel.aspx
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AgendaWhat is Azure? This is Collab365 - You got this!What is Machine Learning?What is AzureML?DataMarket.AzureApplication IntegrationAPI/Data Management
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What is Azure API Management?• http://azure.microsoft.com/en-us/documentation/articles/a
pi-management-get-started/
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What is Azure Data Factory?• http://azure.microsoft.com/en-us/services/data-factory/
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Review• Azure• Machine Learning• AzureML• DataMarket.Azure• Application Integration• API/Data Management
• Questions?
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Resourceshttp://MicrosoftVirtualAcademy.comhttp://channel9.msdn.comhttp://blogs.technet.com/b/machinelearning/
DataMarket.Azure.comText Analytics – SentimentTwitter Sentiment AnalysisLexicon Based Sentiment Analysis
Connect with me! Twitter: @DavidWalker, LinkedIn, Facebook, http://RadicalDave.com