Roadmap to Machine Learning
Webinar Presented by AWS and PREDICTif
Have you wanted to hear insights from trusted and experienced Data Scientists on how it all works? Then you don’t want to miss our webinar where you’ll engage with two accomplished Data Scientists on how they leveraged machine learning and artificial intelligence technologies to enhance business processes at Smith & Associates, a global leading semi-conductor distribution company. The scientists will share their experience using a variety of cloud-based data science technologies as well as best practices – the real do’s and don’ts! They will also illustrate how they have applied the technologies to real-life use cases to show how Smith has benefited from data science. You’ll leave this interactive session with more knowledge on machine learning, helping you to embark on your own journey.
who should attend
Anyone interested in machine learning/artificial intelligence or data science, Data Scientists, Analytics Directors, IT Professionals, IT Managers, line of business users
July 16, 2020 | 11:00 AM CDT
Lead Data Scientist
Eric Lehman is a Lead Data Scientist at Smith & Associates, a global leading semi-conductor distribution company. Eric has led numerous data science and analytics initiatives and built a state-of-art ML/AI platform to support and enhance Smith’s sales, marketing, and operations processes. Prior to embarking on a career in Data Science, Eric received two Bachelor of Science degrees in Petroleum Engineering and Aerospace Engineering from The University of Texas. He spent most of his career in oil and gas and aeronautics. Eric became increasingly interested in Data Analytics and Machine Learning, leading him to obtain his MS in Analytics from the University of San Francisco. He then had an Analyst position with the Houston Astros to develop optimal numerical representations of the “real” strike zone for different pitch counts, batter heights and batter stances.
Director of Data Science
David Hren is the Director of Data Science at PREDICTif Solutions. He provides leadership for project delivery as well as solution and IP development at PREDICTif’s Data Science practice. Before joining PREDICTif, David worked in the oil/gas industry where he gained extensive hands-on experience implementing data-driven solutions. David has a strong technical background, with a Ph.D. in mathematics from New Mexico State University, and he enjoys the challenge of utilizing math and technology to generate business solutions.
Partner Solutions Architect
Stephen Mayne is a Partner Solutions architect who works with partners to develop solutions that take advantage of the AWS Platform. He works with partners to help see out the AWS Machine Learning vision: to put Machine Learning in the hands of every developer and data scientist. He also works in the developing machine learning field, helping to build deployment and automation pipelines for production ML services.