Data Science

2. Leveraging
The Power of AI

3. 1. What is artificial intelligence?

7. Flexible infrastructure
support for analytics
Best of Microsoft research
and open source
Most comprehensive
data science capabilities
Easy to consume
Artificial Intelligence
Solutions Extensible applications

8. Services
Processing
Frameworks
CPUs
AI Applications
Cognitive Services
Infrastructure
AML Web Services BOT Framework
Model & Experimentation
Management
Spark AI Batch
Training
Storage
COSMOS DB ADLSSQL DB SQL DWBLOB
GPUs
FPGA
IOT
Inferencing
Spark, SQL,
Other Engines
DSVM
EDGE
PROSE Data Wrangling
Machine Learning Toolkits
CNTK Tensorflow ML Server Scikit-Learn Other Libs.
ACS
Docker

9. Microsoft AI
Agent Applications Services Infrastructure
For every person and every organization

10. Agent

11. StreamComplexityConversations
Applications Non-standard Resources

12. Applications
Office 365
SwiftKey
Pix
Customer Service and Support
Dynamics 365
Skype
Teams
Calendar.help

13. Services
Bot Framework
Cognitive Services
Cognitive Toolkit (CNTK)
Cortana Intelligence
Cortana Devices SDK

14. Infrastructure
Azure N Series
FPGA

15. Roll-your-own with REST APIs
Simple to add: just a few
lines of code required
Integrate into the language
and platform of your choice
Breadth of offerings helps you
find the right API for your app
Bring your own data for your
custom experience
Built by experts in their field
from Microsoft Research, Bing,
and Azure Machine Learning
Quality documentation, sample code,
and community support
Easy Flexible Tested
Why Microsoft
Cognitive Services?
KLUCZ
TWÓRZ

16. Microsoft Cognitive Services
Give your apps a human side

17. Microsoft Cognitive Services
Give your apps a human side
KnowledgeLanguage LabsSearch
Computer Vision
Content Moderator
Emotion
Face
Video
Video Indexer
Project Prague
(gesture)
Project Cuzco (events)
Project Johannesburg
(routing)
Project Nanjing
(isochrones)
Project Abu Dhabi
(distance matrix)
Project Wollongong
(location)
Bing
Autosuggest
Bing Image
Search
Bing News
Search
Bing Video
Search
Bing Web Search
Bing Entity
Search
Academic
Knowledge
Entity Linking
Knowledge
Exploration
Recommendations
QnA Maker
Bing Spell Check
Linguistic Analysis
Text Analytics
Translator Text
& Speech
Web Language
Model
Bing Speech
Speaker
Recognition

20. Conversation as
a Platform

21. Customer Service and Support
Make Customer Service Bots more
human and Live Agents more
productive with Enterprise level AI.
I am having trouble setting up a new projector
with my laptop

23. Engage with your users where they already are
Bot Framework: a natural language interface across all conversation channels
Provide information
Perform tasks
Make recommendations
Capture information
OperationalizationInsights

24. Bot Directory
Your Bot Framework
Try, use, and add published bots to the
world’s top conversation experiences.
Developer Portal
Connect your bots to text/sms, Skype,
Slack, Facebook Messenger,
Office 365 mail and other channels.
• Register, connect, publish and
manage your bot through your
bot’s dashboard
• Automatic card normalization
across channels
• Skype channel auto-configured
• Embeddable Web chat control
• Host your bot in your app via
the Direct Line API
• Fast, scalable message routing
• Diagnostic tools
Bot Builder
Tools and services to build great bots
that converse wherever your users are.
• Open source SDK on Github for
Node.js, .NET and REST
• From simple built-in prompts
and command dialogs to
simple to use yet sophisticated
‘FormFlow’ dialogs
• Support for rich attachments
(image, card, video, doc, etc.);
support for calling (Skype)
• Online/offline chat Emulator
• Add bot smarts with Cognitive
Services for language
understanding and more
• Public directory of bots
registered and published with
Microsoft Bot Framework
• Users can try your bot from the
directory via the Web chat
control
• Users can discover and add
your bot to the channels on
which it is configured when the
Directory is made public to end
users

25. Cognitive Toolkit
Unlock deeper learning
A free, easy-to-use, open-source toolkit that
trains deep learning algorithms to learn like the
human brain.
Microsoft Cognitive Toolkit

29. Apps + insights
Social
LOB
Graph
IoT
Image
CRM INGEST STORE PREP & TRAIN MODEL & SERVE
Data orchestration
and monitoring
Data lake
and storage
Hadoop/Spark/SQL
and ML
.
IoT
Azure Machine Learning
T H E A I D E V E L O P M E N T L I F E C Y C L E

30. Azure Machine Learning Studio
Platform for data scientists to graphically
build and deploy experiments
 Rapid experiment composition
 > 100 easily configured modules for
data prep, training, evaluation
 Extensibility through R & Python
 Serverless training and deployment
Some numbers:
 100’s of thousands of deployed models
serving billions of requests

31. What have we learned?
Customers have told us they love the convenience…
…Customers have told us they need:
 Greater control over compute & data
 More options for model deployment
 Which frameworks? ALL OF THEM!

32. Notebooks
IDEs
Azure Machine Learning
Workbench
VS Code Tools for AI
N E W C A P A B I L I T I E S
Experimentation and
Model Management
Services
AZURE MACHINE
LEARNING SERVICES
 Spark
 SQL Server
 Virtual
machines
 GPUs
 Container
services
 SQL Server
 Machine Learning
Server
ON-PREMISES
EDGE
 Azure IoT
Edge
TRAIN & DEPLOY
OPTIONS
AZURE

33. What Did I Get?
Experimentation Account:
 Keep track of projects
 Local, scale-up, and scale-out training
 Run history tracking
Model Management Account:
 Create containers for models
 Manage and monitor deployed models

34. Local machine
Scale up to DSVM
Scale out with Spark on HDInsight
Azure Batch AI (Coming Soon)
ML Server
Experiment Everywhere
A ZURE ML
EXPERIMENTATION
Command line tools
IDEs
Notebooks in Workbench
VS Code Tools for AI

35.  Manage project dependencies
 Manage training jobs locally, scaled-up or
scaled-out
 Git based checkpointing and version control
 Service side capture of run metrics, output
logs and models
 Use your favorite IDE, and any framework
Experimentation service
U S E T H E M O S T P O P U L A R I N N O VAT I O N S
U S E A N Y TO O L
U S E A N Y F R A M E W O R K O R L I B R A R Y

36. DOCKER
Single node deployment
(cloud/on-prem)
Azure Container Service
Azure IoT Edge
Microsoft ML Server
Spark clusters
SQL Server
Deploy Everywhere
A ZURE ML
MODEL MANAGEMENT

37.  Deployment and management of models as
HTTP services
 Container-based hosting of real time and
batch processing
 Management and monitoring through Azure
Application Insights
 First class support for SparkML, Python,
Cognitive Toolkit, TF, R, extensible to support
others (Caffe, MXnet)
 Service authoring in Python
Manage models

39.  Windows and Mac based
companion for AI development
 Full environment set up (Python,
Jupyter, etc)
 Embedded notebooks
 Run History and Comparison
experience
 New data wrangling tools
What Is It?

40. AI Powered Data Wrangling
 Rapidly sample, understand,
and prep data
 Leverage PROSE and more for
intelligent, data prep by
example
 Extend/customize transforms
and featurization through
Python
 Generate Python and Pyspark
for execution at scale

41. Machine Learning & AI Portfolio
When to use what?
What engine(s) do you want
to use?
Deployment target
Which experience do you
want?
Build your own or consume pre-
trained models?
Microsoft
ML & AI
products
Build your
own
Azure Machine Learning
Code-first
(On-prem)
ML Server
On-
prem
Hadoop
SQL
Server
(cloud)
AML services (Preview)
SQL
Server
Spark Hadoop Azure
Batch
DSVM Azure
Container
Service
Visual tooling
(cloud)
AML Studio
Consume
Cognitive services, bots

42. The most critical next step
in our pursuit of A.I. is to
agree on an ethical and
empathic framework for
its design.
SATYA NADELLA