azure machine learning. fast start
TRANSCRIPT
Microsoft Azure MLMachine Learning as a
Service
Dmitry PetukhovResearcher, Developer && Coffee Addict @ OpenWay
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Azure Machine Learning. Introduction
S
Cloud ComputingBig Data
Machine Learning
Microsoft AzureFeb. 2015: Azure Machine Learning in GA
Predictive analytics services
Amazon Web ServicesApr. 2015: Amazon Machine Learning in GA
Google Cloud PlatformOct. 2015: Google Cloud Datalab in Beta
Storage
ResourceManagement
ML Framework
Execution Engine
Local OS
Local Disc
Pyth
on
Runt
ime
Yet A
noth
er
Runt
ime
scikitlearn
HDFS
YARN
MapReduce
Mahout
HDFS / S3
YARN / Apache Mesos
Spark
MLlib
HDFS / S3
YARN / Apache Mesos
Python / R on Spark
Python / Rtools
Spark
Distributed FS
Dark Magic…
Local PC Hybrid Model Cluster (on-premises/cloud)ML as a Service
(cloud)
Challenge
somelibrar
yPython / R
tools
Step 3. Create Azure ML WorkspaceStep 4. Go to Azure ML Studio & create ML Experiment Step 5. Publish result
Azure Machine Learning. Overview
Hello Azure ML!
Step 1. Get $200 creditSign up for Azure free trial.
Step 2. Get access to Azure Portal
Reduce complexity to broaden participationNo software to install, only web browser;Possibility to develop without writing line of code;Easy deployment and usage using restfull API;Easy collaboration on Azure ML projects;Visual composition with end2end support for Data Science
workflow;Extensible, support for R OSS.
Data Science is far too complex today
Knowledge in Mathematics &Knowledge in Computer Science &Domain Expert &…what else?!
Reference: TechEd 2014 Conference
Azure Machine Learning. Overview
Guiding Principles
Data Azure Machine Learning Consumers
Local storageUpload data from
PC…
Cloud storageRDBMSNoSQLHDFSetc.
Power BI
Business Apps
Reference: TechEd 2014 Conference
Azure Machine Learning. Overview
Business problem Modeling Business valueDeployment
Azure Marketplace(Applications
store)Azure ML Gallery
(community)
ML Web Services(REST API Services)
ML Studio(Web IDE)
Workspace:ExperimentsDatasetsTrained modelsNotebooksAccess settings
Data Model API
Manage API
Azure Machine Learning. Azure ML Flow
Supervised Learning FlowPart #1
Azure Machine Learning. Azure ML Flow
Supervised Learning FlowPart #2
Source: http://0xCode.in/azure-ml-for-data-scientistThis work is licensed under a Creative Commons Attribution 4.0 International License
Supervised Learning FlowPart #2
Azure Machine Learning. Azure ML Flow Source: Azure ML Cheat Sheet
DemoTwitter sentiment
analysis
Azure Machine Learning. Demo
Source: Wikipedia
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 20 concurrent request per endpointMax endpoints count: 10K
Black boxNo debugNo Scala, or C++, or C# No your own “right” algorithms
Azure Machine Learning. Conclusion
Killer Features
R (quickstart)Support R models & scripts
Python (quickstart)Support Python scriptsJupyter Notebooks in Azure ML Studio
PublishingREST API & real-time mode vs batch-mode
Azure ML 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 Machine Learning. Conclusion
References
Start from azure.com/ml
Microsoft Machine Learning Blog
Azure ML documentation +free online course, videos & books
For Researchers: Azure for Researchers
28-29 Nov.: Microsoft Machine Learning Hackathon
Azure Machine Learning. Conclusion
© 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: @codezombieFacebook: @code.zombi
LinkedIn: @dpetukhovAll contacts…
Read my tech code instinct blog on http://0xCode.in/
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Azure ML: Machine Learning as a Service