Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

Meet the Experts

Meet the Experts gives you a chance to meet face-to-face in a small group setting with expert Strata Data Conference presenters. Discuss the speaker's area of expertise, give feedback about their sessions, or ask questions. Meet the Experts will take place in the Expo Hall.

    Wednesday, September 27

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    11:20am12:00pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table A)
    Michael Li (The Data Incubator)
    Michael will answer questions about building a data-driven culture. Read more.
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    11:20am12:00pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table B)
    Cathy O'Neil (Weapons of Math Destruction)
    Mathematical models shape our future—scoring teachers and students, sorting résumés, granting (or denying) loans, evaluating workers, targeting voters, setting parole, and monitoring our health. Join Cathy for a spirited discussion about what this means for individuals and our society. Read more.
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    1:15pm1:55pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table A)
    David Talby (Pacific AI)
    Got questions on applying machine learning, natural language processing, and deep learning, especially in the domains of healthcare and life sciences? Stop by and meet David. Read more.
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    2:05pm2:45pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table A)
    Mike Driscoll (Metamarkets)
    If you're interested in data in programmatic marketing, Mike has a wealth of information on how to get it right. Read more.
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    2:05pm2:45pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table B)
    Rebecca S. Bilbro (ByteCubed)
    Rebecca will be on hand to share practical advice on text analytics and suggestions for open source machine learning packages and chat about real-world use cases as they relate to text data and NLP in everyday applications. Read more.
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    2:55pm3:35pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table A)
    Eric Colson (Stitch Fix)
    Stop by to meet Eric to get ideas on how manage your data science team to foster innovation and how to transform a data science team that merely serves a supportive role to one that leads with data science. Read more.
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    3:45pm4:25pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table A)
    Michelle will be on hand to discuss SAP Data Hub solutions, challenges for building comprehensive data pipelines, and data orchestration and execution. Read more.
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    4:35pm5:15pm Wednesday, September 27, 2017
    Location: O'Reilly booth (Table A)
    Holden Karau (Google)
    Do you have Apache Spark questions (especially about Python, performance, or ML)? Come chat with Holden. Read more.

    Thursday, September 28

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    11:20am12:00pm Thursday, September 28, 2017
    Location: O'Reilly booth (Table B)
    Jesse Anderson (Big Data Institute)
    Jesse will talk to you about creating data engineering teams that are productive and create excellent data products. Read more.
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    11:20am12:00pm Thursday, September 28, 2017
    Location: O'Reilly booth (Table A)
    Matthew Rocklin (Anaconda)
    Want to know how to parallelize Python code with Dask? Talk to Matthew. Read more.
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    1:15pm1:55pm Thursday, September 28, 2017
    Location: O'Reilly booth (Table A)
    Dean Wampler (Lightbend)
    Join Dean to discuss all things streaming, especially with Kafka, Spark, Flink, Akka Streams, and Kafka Streams—from the future of machine learning in a streaming context to integrating stream processing with microservices. Read more.
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    2:05pm2:45pm Thursday, September 28, 2017
    Location: O'Reilly booth (Table A)
    Michael Freedman (TimescaleDB | Princeton)
    Talk with Michael about handling time series data across an organization. (Hint: it's not just for DevOps.) Read more.
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    2:55pm3:35pm Thursday, September 28, 2017
    Location: O'Reilly booth (Table A)
    Ted Dunning (MapR Technologies)
    Ted is happy to talk with you about stream-first architecture, machine learning logistics, and recent developments in t-digest. Read more.