![Data Engineering
Data Science Business Analysis App Development
Data Sources
• On-premises / cloud
• Structured / unstructured
[and content repositories]
• In-motion / at-rest
• Internal / external Hadoop
NoSQL / SQL
Object store
Discovery / Exploration
Machine learning
Model development
Reports / Dashboards
Applications
APIs
Integration
Matching / Quality
Streaming
Persist
Analyze
Ingest Deploy
Iterate
Govern
Data Assessment
Metadata / Policies
Find Share Collaborate
Intelligent Data Fabric
IBM Watson Data Platform
Watson Developer Cloud
APIs
•Natural Language
•Vision Services
•Data Insight Services](https://image.slidesharecdn.com/dsxandwml-andrewzhangchicagodatascienceconferencefinal-170530182107/85/IBM-Data-Science-Experience-and-Machine-Learning-Use-Cases-in-Healthcare-3-320.jpg)
![© 2016 IBM Corporation33
Legal Disclaimer
• © IBM Corporation 2015. All Rights Reserved.
• The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained
in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this information is based on IBM s current product plans and strategy, which are
subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this publication or any other materials. Nothing
contained in this publication is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and
conditions of the applicable license agreement governing the use of IBM software.
• References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or
capabilities referenced in this presentation may change at any time at IBM s sole discretion based on market opportunities or other factors, and are not intended to be a commitment
to future product or feature availability in any way. Nothing contained in these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by
you will result in any specific sales, revenue growth or other results.
• If the text contains performance statistics or references to benchmarks, insert the following language; otherwise delete:
Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will
experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage
configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.
• If the text includes any customer examples, please confirm we have prior written approval from such customer and insert the following language; otherwise delete:
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purposes only.](https://image.slidesharecdn.com/dsxandwml-andrewzhangchicagodatascienceconferencefinal-170530182107/85/IBM-Data-Science-Experience-and-Machine-Learning-Use-Cases-in-Healthcare-18-320.jpg)
IBM Data Science Experience and Machine Learning Use Cases in Healthcare
- 1. Andrew Zhang – Cloud Analytics Architect, IBM Data Science Experience Chicago Data Science Conference – 5.20.2017
- 3. Data Engineering Data Science Business Analysis App Development Data Sources • On-premises / cloud • Structured / unstructured [and content repositories] • In-motion / at-rest • Internal / external Hadoop NoSQL / SQL Object store Discovery / Exploration Machine learning Model development Reports / Dashboards Applications APIs Integration Matching / Quality Streaming Persist Analyze Ingest Deploy Iterate Govern Data Assessment Metadata / Policies Find Share Collaborate Intelligent Data Fabric IBM Watson Data Platform Watson Developer Cloud APIs •Natural Language •Vision Services •Data Insight Services
- 4. Retrieve and Rank Easy access to Cognitive building blocks 4 Entity Extraction Sentiment Analysis Emotion Analysis (Beta) Keyword Extraction Concept Tagging Taxonomy Classification Author Extraction Language Detection Text Extraction Microformats Parsing Feed Detection Linked Data Support Concept Expansion Concept Insights Dialog Document Conversion Language Translation Natural Language Classifier Personality insights Relationship Extraction Retrieve and Rank Tone Analyzer Emotive Speech to Text Text to Speech Face Detection Image Link Extraction Image Tagging Text Detection Visual Insights Visual Recognition AlchemyData News Tradeoff Analytics 50+ underlying technologies Natural Language C lassifier Tone Analyzer
- 6. IBM Data Science Experience Community Open Source IBM Added Value Powered by IBM Watson Data Platform • Find tutorials and datasets • Connect with Data Scientists • Ask questions • Read articles and papers • Fork and share projects • Code in Scala/Python/R/SQL • Jupyter Notebooks • RStudio IDE and Shiny • Spark ML • Your favorite libraries • Managed Spark Service • Project, Catalog, Data Connect • ML Model Builder and Canvas • IBM Machine Learning API • Cloud, Desktop and Local Deployment Core Attributes of the Data Science Experience
- 10. Amazon ML
- 13. IBM Machine Learning in Data Science Experience API for Jupyter Notebooks Model Builder GUI IBM Machine Learning is provisioned by default in Data Science Experience • Enables Data Scientists to deploy machine learning models as web services • Single UI for creating, collaborating, deploying, monitoring, and feedback • Accessible via API, Wizard GUI, and Canvas Data Scientist Canvas Stream
- 14. Bluemix Experience for the App Developer Simple UI driven by REST APIs • Train models • Save models to a WML Repository • Deploy models – batch, real-time, streaming • Score data Swagger documentationBluemix dashboard
- 17. Demo
- 18. © 2016 IBM Corporation33 Legal Disclaimer • © IBM Corporation 2015. All Rights Reserved. • The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this information is based on IBM s current product plans and strategy, which are subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this publication or any other materials. Nothing contained in this publication is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use of IBM software. • References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or capabilities referenced in this presentation may change at any time at IBM s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to future product or feature availability in any way. Nothing contained in these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales, revenue growth or other results. • If the text contains performance statistics or references to benchmarks, insert the following language; otherwise delete: Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here. • If the text includes any customer examples, please confirm we have prior written approval from such customer and insert the following language; otherwise delete: All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics may vary by customer. • Please review text for proper trademark attribution of IBM products. At first use, each product name must be the full name and include appropriate trademark symbols (e.g., IBM Lotus® Sametime® Unyte™). Subsequent references can drop IBM but should include the proper branding (e.g., Lotus Sametime Gateway, or WebSphere Application Server). Please refer to http://www.ibm.com/legal/copytrade.shtml for guidance on which trademarks require the ® or ™ symbol. Do not use abbreviations for IBM product names in your presentation. All product names must be used as adjectives rather than nouns. Please list all of the trademarks that you use in your presentation as follows; delete any not included in your presentation. IBM, the IBM logo, Lotus, Lotus Notes, Notes, Domino, Quickr, Sametime, WebSphere, UC2, PartnerWorld and Lotusphere are trademarks of International Business Machines Corporation in the United States, other countries, or both. Unyte is a trademark of WebDialogs, Inc., in the United States, other countries, or both. • If you reference Adobe® in the text, please mark the first use and include the following; otherwise delete: Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries. • If you reference Java™ in the text, please mark the first use and include the following; otherwise delete: Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates. • If you reference Microsoft® and/or Windows® in the text, please mark the first use and include the following, as applicable; otherwise delete: Microsoft and Windows are trademarks of Microsoft Corporation in the United States, other countries, or both. • If you reference Intel® and/or any of the following Intel products in the text, please mark the first use and include those that you use as follows; otherwise delete: Intel, Intel Centrino, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. • If you reference UNIX® in the text, please mark the first use and include the following; otherwise delete: UNIX is a registered trademark of The Open Group in the United States and other countries. • If you reference Linux® in your presentation, please mark the first use and include the following; otherwise delete: Linux is a registered trademark of Linus Torvalds in the United States, other countries, or both. Other company, product, or service names may be trademarks or service marks of others. • If the text/graphics include screenshots, no actual IBM employee names may be used (even your own), if your screenshots include fictitious company names (e.g., Renovations, Zeta Bank, Acme) please update and insert the following; otherwise delete: All references to [insert fictitious company name] refer to a fictitious company and are used for illustration purposes only.