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Innovation: a definition
«Innovation is the ability to
create value while bringing
something new in the field and
ensuring that the appropriation
of this novelty is optimum.»
Arnaud Groff, Dr in
« Management de l'Innovation & de la
Créativité »
Microsoft Research (MSR)
Redmond (1991) Cambridge (1997) Beijing (1998)
Silicon Valley (2001) Bangalore (2005) New England (2008)
More than 1,100 brilliant scientists and engineers push the boundaries of
computing in multiple research areas and include contributions to Kinect for
Xbox 360, work to develop an HIV vaccine, and advancing education
techniques in rural communities.
4ème mondial toute industrie confondue
1er mondial dans l’industrie du logiciel
Microsoft Research scientists have
won more than 320 major awards,
including the Turing Award, MacArthur
Foundation Fellowship, MIT
Technology Review’s TR35 Award, the
Draper Prize, IEEE John von Neumann
Medal, IEEE Piore Award, the Kyoto
Prize, multiple Oscars and a British
knighthood.
Microsoft Research Awards
Joint research institutes
INRIA, France
Software security; Formal methods;
Applications of computer science
research to science
www.msr-inria.inria.fr
University of Trento, Italy
Computational tools for systems
biology
www.cosbi.eu
Barcelona Super
Computing Centre, Spain
Multi core systems; Architectures and
programming; Language runtimes
www.bscmsrc.eu
Algorithms and TheoryExploring the theoretical foundations of computing, and efficient
algorithms for a wide variety of problems.
Communication and CollaborationEnabling people to reach each other easily regardless of network
or device.
Computational LinguisticsFocusing on machine translation, multilingual systems
and natural-language processing.
Computational ScienceProviding computational support to unravel the
mysteries of the universe.
Computer Systems and NetworkingImproving efficiency in the deployment, operation management and
security of distributed applications.
Computer VisionTeaching computers to see and
understand the visual world.
Data Mining and ManagementCreating systems for accessing and managing large collections of data,
and algorithms for finding patterns and insights within the data.
Economics and ComputationExploring the connections between economics and
computer science, and creating economic models of
online systems.
EducationApplying computing to help people learn. Expanding
programs in computer-science education.
GamingExploring new technologies to enhance the gaming experience, and
identifying and developing innovative technologies and curricula to
aid in educational activities.
Graphics and MultimediaAddressing challenges in displaying complex computer graphics
models, in multiresolution signal representations and enhancement,
and in compression of geometry and multimedia data.
Hardware and DevicesBuilding the hardware that will support the
next generation of software.
Health and Well-BeingLeading innovation in assisted cognition, bioinformatics,
synthetic biology, and biomedicine.
Human-Computer InteractionAdvancing the way users interact with computing
devices.
Machine Learning and IntelligenceBuilding software that automatically learns from data to create
more advanced, intelligent computer systems.
Mobile ComputingExploring how to build mobile devices and services that
are efficient, responsive, and usable.
Quantum ComputingExploiting quantum physics to create a new
generation of computing devices.
Search, Information Retrieval and
Knowledge ManagementExploring indexing and classification technologies, entity extraction, and user-
experience concepts that help people organize and find information.
Security and PrivacyEnsuring the privacy and integrity of our
computations and data.
Social MediaExploring how digital media are changing the way people
work, play, and connect with each other.
Social ScienceExploring how people use
computing in their daily lives.
Software Development, Programming
Principles, Tools, and LanguagesImproving quality and efficiency throughout the software-development
process.
Speech Recognition, Synthesis,
and Dialog SystemsTeaching computers how to both speak and listen.
Technology for Emerging MarketsUnderstanding how technologies can address the needs and
aspirations of people in the world’s developing communities.
Machine Learning and IntelligenceBuilding software that automatically learns from data to
create more advanced, intelligent computer systems.
intelligence will become ambient
intelligence from machine learning
Qu’est-ce que le Machine Learning ?
Des méthodes et des systèmes qui …
en fonction
des données
collectées
de nouvelles
données en
fonction des
données
collectées
une action
étant donné
une fonction
d’utilité
une structure
cachée des
données
les données
en des
descriptions
concises
s’adaptent prédisent optimisent extraient résument
Champ d’études qui donne aux ordinateurs la capacité
d’apprendre sans avoir besoin d’être explicitement programmés
20 ans de Machine Learning chez Microsoft
1992
début de la
reconnaissance vocale2000
système de
recommandation dans
Commerce Server
2005
Data Mining dans
SQL Server 2005
2008
Kinect pour XBOX
2009
Flash Fill pour Excel 2013
2014
Microsoft Azure
Machine Learning
from Machine Learning to Predictive Analysis
In business, predictive models exploit patterns
found in historical and transactional data to
identify risks and opportunities
Crime Fighting
Fraud Detection
Marketing
Advertising
Family and
Personal Life
Human Resources
Financial Risk
InsuranceHealthcare
Fault Detection for
Safety and Efficiency
Questions connexes à prendre compte
Prédire les prochains souscripteurs de crédit automobile
Modèle
comporte-
mental
Caractéristiques
Succession
d’événementsContexte
Social
Je suis un cadre dans
l’informatique de 42 ans,
propriétaire de ma
résidence, avec 2
enfants…
… j’ai réalisé deux
dépenses de puériculture
supérieures à 200€
chacune dans les trois
derniers mois…
…mes amis viennent de
souscrire des crédits
automobile…
…dans trois semaines
aura lieu le salon de
l’automobile Porte de
Versailles…
ThyssenKrupp ElevatorThyssenKrupp Elevator wanted to gain a competitive edge by focusing on what matters most to its customers in buildings the world over: reliability
Pier 1 ImportsPier 1 Imports discuss how they predict which product the customer might want to purchase next, helping to build a better relationship with their customers.
London UndergroundBringing the Internet of Things to the London Underground
Mission Critical Systems
Business Analytics
Predictive Analysis
Ambiant Intelligence for a better Customer Experience“Consistent, Personalized, and Self-learning”
Customer
Business Operations
Orders / CRM
Inventory / IOT
Finance
Services
External sources
Rating
Social / Weather
Demographics
PartnersIntegrated Enterprise Data
Single View of the Customer
Information as a service
Scores Segmentation
High-Value Services
Sales
Campaign
Churn
Prices
Interaction
Management
Channels
Web
Stores
Support
Devices
Lounges
Partners
Learning
Ambiant Intelligence for a better Customer Experience“Consistent, Personalized, and Self-learning”
Customer
Business Operations
Orders / CRM
Inventory / IOT
Finance
Services
External sources
Rating
Social / Weather
Demographics
PartnersIntegrated Enterprise Data
Single View of the Customer
Information as a service
Scores Segmentation
High-Value Services
Sales
Campaign
Churn
Prices
Interaction
Management
Channels
Web
Stores
Support
Devices
Lounge
Partners
Learning
Advanced and Innovative Dashboards from any device
Crunching des données
internes / externes2
Mode opératoire standard pour un projet ML
Compréhension du métier et
des données de nos clients1
Vérification itérative
avec les métiers4Mise en production du
modèle prédictif final5
Mise au point des
modèles mathématiques3
Apprentissage supervisé
70%
30%
« La fiabilité du
modèle est de 93% »
Test
Apprentissage
Apprentissage non supervisé
Frauduleux
Suspects
Légitimes
Apprentissage non supervisé
Légitime
Frauduleux
Suspects
Légitimes
Frauduleux
BIG DATA / MACHINE LEARNING : un état d’espritTypologie simplifiée des projets Big Data / Machine Learning
Expérimentation
Big Data (Data Lab)
Industrialisation de la
production d’indicateurs
Focalisé sur la production
rapide de résultatsFocalisé sur les moyens
Scientifique
(Exploratoire)
Ingénieur
(Top-Down ou Bottom-Up)
Disruption,
Accepter l’erreur
Continuité,
Aversion au risque
Métiers
« Shadow IT »
IT
« Core IT »
Métiers & IT
« Fast IT »
≠
Business Value WorkshopLa Data Science au service de vos métiers
MICROSOFT
SERVICES
De la Data aux Insights : quels scénarios innovants pour mieux exploiter les données ?
Introduction autour des nouvelles tendances et enjeuxdu marché ainsi que de la vision de Microsoft sur la Data Science
Compréhension des enjeux métiers du client et des données manipulées par celui-ci
Recensement des intuitions du client
Identification des questions « Machine Learning » intéressant le client et valorisation de celles-ci
Choix de la question la plus pertinente et proposition de pilote pour y répondre
Agenda – ½ journée
Problématique
Accompagnement sur la mise en place des scénarios identifiés
Objectif de l’atelier :
• Présenter les tendances et nouveaux usages autour des données ainsi que les opportunités offertes par la Data Science avec Microsoft
• Imaginer et formaliser un ou plusieurs scénarios cibles pour répondre à vos problématiques métiers
Vue d’ensemble
Préparation :
• Identification d’un sponsor client, puis des participants à inviter
• Rendez-vous de qualification avec le sponsor, 1h pour identifier ses enjeux et définir sa problématique
Audience attendue :
Pour plus d’informations : [email protected]
Fully
managed
Integrated Flexible Deploy in
minutes
No software to install,
no hardware to
manage, all you need is
an Azure subscription.
Drag, drop and
connect interface.
Data sources with just
a drop down; run
across any data.
Built-in collection of
best of breed
algorithms with no
coding required. Drop
in custom R or use
popular CRAN
packages.
Operationalize models
as web services with a
single click.
Monetize in Machine
Learning Marketplace.
Business users access results from anywhere, on any device
Delivering Advanced Analytics
• HDInsight
• SQL Server VM
• SQL DB
• Blobs & Tables
Devices Applications Dashboards
Data Microsoft Azure Machine Learning
Storage space
Integrated development environment for Machine
Learning
ML
Studio
Business challenge Business valueModeling Deployment
• Desktop files
• Excel spreadsheet
• Other data files on PC
Cloud
Local
Data to model to web services in minutes
http://studio.azureml
.net
Web
Clients
API
Model is now a web svc
Monetize this API
Drag & Drop + Best in Class Algorithms
API examples
Green Score, Wealth Score, Giving Score
Frequently Bought Together API
Recommendations API
Anomaly Detection API
Lexicon Based Sentiment Analysis
Forecasting-Exponential Smoothing
Forecasting - ETS+STL
Forecasting-AutoRegressive Integrated Moving Average (ARIMA)
Binary Classifier API
Cluster Model API
Survival Analysis API
Multivariate Linear Regression API
Survival Analysis API
Multivariate Linear Regression API
Normal Distribution Quantile Calculator
Binomial Distribution Quantile Calculator
datamarket.azure.com
