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Machine Learning in Microsoft Azure
Dmitry Petukhov,Researcher & Developer @ OpenWay
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Azure ML for Developers: Machine Learning in our Life
Web
Social Networ
ksScience
Healthcare
Finance
Telecom
Retail
Logistic
Security
Electronics
Proof: https://www.kaggle.com/wiki/DataScienceUseCases
Business ScenariosRecommendations,customer churn,forecasting, etc.
Perceptual IntelligenceFace, vision
Speech, text
Dashboards and Visualizations
Power BI
Machine Learning
and AnalyticsAzure Machine Learning
Azure HDInsight (Hadoop)
Azure Stream Analytics
DATA
Business apps
Custom apps
Sensors and devices
INTELLIGENCE CONSUMERS
People
Automated Systems
Big Data Stores
Azure Data LakeAzure SQL Data Warehouse
Information Management
Azure Data Factory
Azure Data Catalog
Azure Event Hub
Reference: Microsoft Ignite 2015
Personal Digital Assistant
Cortana
Cortana Analytics Suite
Azure ML for Developers: Cortana Analytics Stack
Business ScenariosRecommendations,customer churn,forecasting, etc.
Perceptual IntelligenceFace, vision
Speech, text
Dashboards and Visualizations
Power BI
Machine Learning
and AnalyticsAzure Machine Learning
Azure HDInsight (Hadoop)
Azure Stream Analytics
DATA
Business apps
Custom apps
Sensors and devices
INTELLIGENCE CONSUMERS
People
Automated Systems
Big Data Stores
Azure Data LakeAzure SQL Data Warehouse
Information Management
Azure Data Factory
Azure Data Catalog
Azure Event Hub
Source: Microsoft Ignite 2015
Personal Digital Assistant
Cortana
Azure ML for Developers: Machine Learning Use Cases in Banking
Financial Markets & etc. Retail Banking Insurance
Real-time Batch processingDuration
Market Assets Price
Prediction
Social Network Analysis
Fraud Detection
Risk Analysis
Compliance &
Regulatory Reporting
Advertising Campaign Optimizati
on
News Analysis
Customer Loyalty & Marketing
Improving operation
al efficiencie
s
Credit Scoring
Brand Sentiment Analysis
Personalized Product
Offering
Customer Segmentati
on
Reference: http://0xcode.in/big-data-in-banking
Azure ML for Developers: Machine Learning Use Cases in Banking
Financial Markets & etc. Retail Banking Insurance
Real-time Batch processingDuration
Market Assets Price
Prediction
Social Network Analysis
Fraud Detection
Risk Analysis
Compliance &
Regulatory Reporting
Advertising Campaign Optimizati
on
News Analysis
Customer Loyalty & Marketing
Improving operation
al efficiencie
s
Credit Scoring
Brand Sentiment Analysis
Personalized Product
Offering
Customer Segmentati
on
Reference: http://0xcode.in/big-data-in-banking
СМС атаки на клиентов банков
Закрыто депозитов / текущих счетов на сумму:
Сентябрь 2015 -5 млрд. руб. Декабрь 2014 -1,3 трлн. руб.
Data Azure Machine Learning Consumers
Cloud storageRDBMSNoSQLHDFSAzure
Blobs
Business problem Modeling Business valueDeployment
Azure Marketplace
Data services storeCortana
Analytics Gallerycommunity
ML Web ServicesREST API Services
ML StudioWeb IDE
WorkspaceExperiments
DatasetsTrained
modelsNotebooksAccess
settings
Data Model API
Manage
Azure ML for Developers: Azure Machine Learning Architecture
Local storageUpload data
from PC…
API
Reference: Microsoft Ignite 2015
Azure ML for Developers: Twitter Semantic Analysis Architecture
InternetTwitter
New Tweets ProcessingAzure Worker RolesTwitter App #1
Twitter App #2Twitter App N
Twitter Streaming API
Azure
Semantic PredictionAzure Machine Learning
h(θ0, θn)Semantic prediction APIAzure ML Web Services
REST APIJSON
Final Model
REST APIJSON
h(θ0, θn)Text Analysis ServiceAzure Marketplace
Store results in HBase Azure HDInsight
Stream New Tweet EventsAzure Event Hubs
POST, https
1
2
3
4
5
6
What we do?TD-IDF, short for term frequency–inverse document frequency, is a numerical statistic that is intended to reflect how important a word is to a document in a collection or corpus.
Source: Wikipedia
Azure ML for Developers: Twitter sentiment analysis
What we find?Bank of AmericaCity Bank#DevCampDemo
Microsoft AzureFeb. 2015: Azure Machine Learning (GA)
Amazon Web ServicesApr. 2015: Amazon Machine Learning (GA)
Google Cloud PlatformOct. 2015: Google Cloud Datalab (beta)
Cloud ComputingBig Data
Machine Learning
Machine Learning as a ServiceSLA >99.9%Big Data ready Probably LSML
Azure ML for Developers: Machine Learning as a Service
Restrictions
Legislative restrictionsInternational & local
Azure platform restrictionsMax storage volume per account, etc.
Azure ML service restrictionsData
Max dataset volume: 10 GbVector size limitation: 2^64
Throttled policy 200 concurrent request per endpointMax endpoints count: 10K
Black boxNo debugNo Scala, or C++, or C# No your own “right” algorithmsNo Deep Learning
Azure ML for Developers: Restrictions
R (quickstart)Support R models & scripts
Python (quickstart)Support Python scriptsJupyter Notebooks in Azure ML Studio
PublishingREST API & real-time mode vs batch-mode
Cortana Analytics GalleryShare for community
Azure MarketplaceSaaS store
In-the-box integration with…Hive, Azure Storage, Excel, Cortana Analytics Stack
Free Start & it’s child age
Azure ML for Developers: Killer Features
Start for free from azure.com/ml Read Microsoft Machine Learning BlogExamine Azure ML documentation +free booksTake free MOOCs on MVA and EdXCommunicate on Microsoft Azure Russia group Make the world better place with Azure for Researchers Award program
Azure ML for Developers: References
© 2015 Dmitry Petukhov All rights reserved. Microsoft Azure and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
Thank you!
Q&ANow or later (send on email)
Ping meHabr: @codezombie
LinkedIn: @dpetukhovFacebook: @code.zombi
Read my tech code instinct blog (on http://0xCode.in/)
Download presentation from http://0xcode.in/dev-camp or
Azure ML for Developers: Stay Connected!
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