Transcript
Page 1: Machine Learning in Microsoft Azure

Machine Learning in Microsoft Azure

Dmitry Petukhov,Researcher & Developer @ OpenWay

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⟨Ω ,𝔘 ,ℙ ⟩ #CommunityDevCamp

Page 2: Machine Learning in Microsoft Azure

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

Page 3: Machine Learning in Microsoft Azure

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

Page 4: Machine Learning in Microsoft Azure

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

Page 5: Machine Learning in Microsoft Azure

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

Page 6: Machine Learning in Microsoft Azure

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.

Page 7: Machine Learning in Microsoft Azure

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

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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

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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

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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

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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

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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

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© 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!

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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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