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2017 Conferences - Mark Reynolds

2017 Conferences

Mark Reynolds presented at these Oil and Gas Conferences and .NET and DevOPS events during 2017.

Information Management & AnalyticsUpstream 2017

March 21-23, 2017

Moving towards a Single Version of the Truth throughout the Data Value Chain

  • Making the leap from data into solutions: Understanding data management challenges behind master data and planning data
  • Engineering challenges behind real-time/streaming data sources
  • Limitations of spreadsheets, BI, and user directed research

 

Texas Open Innovation Conference

March 28-29, 2017

Who drives innovation?
The supplier? Or the consumer?

  • Does the supplier drive innovation?
  • Or the Consumer?
  • Why does it matter?

2017 Machine Learning in Oil and Gas Conference

April 19-20, 2018

Road Map to Constructing a Top-Down Big Data and Machine Learning System

E&P organizations are turning more attention to accumulated data to enhance operating efficiencies, safety and recovery. The computing paradigm is shifting, the o&g paradigm is shifting and the rise of the machine learning paradigm requires careful attention to top-down integrated systems engineering. A system approach will be presented to stimulate out-of-the-box thinking to address the machine learning paradigm.

2017 Data Driven Production Conference

June 6-7, 2017

Production Engineering in the 4th Paradigm

Two years ago, Machine Learning, 4th Paradigm, and eScience were seldom discussed in O&G. Today, these topics and the role of data, data knowledge, artificial intelligence are topics found in planning, engineering, and improvement. The promises and pragmatic realities of the 4th Paradigm are explored in this presentation.

Houston Techfest 2017

September 2018

Azure Machine Learning

Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Getting started is easy. The first working prototype is an easy evening project. But Azure Machine Learning will grow to extremely complex projects. This session will demonstrate initial projects utilizing multiple data science principals

 

Houston Techfest 2017

September 2017

Defensive Programming

Will your application be rock solid and maintainable? Common principals are share by most rock solid and maintainable applications.