Building an End to End Solution using Machine Learning – Part 1

The online course will implement an End-to-End Upstream E&P Workflow Solution using Machine Learning (Python knowledge is a pre-requisite). The training session will focus on a Machine Learning workflow in the upstream Oil and Gas domain to generate synthetic Gamma-Ray Logs by applying Artificial Intelligence (AI) Techniques, learning the various aspects of deploying this workflow in an end-to-end solution that a Geoscientist can use.
The course is split in two webinar sessions.

Part 1: Identify use case and pain points, Identify and collect the relevant data.

Part 2: Build/Train and test the Machine Learning Model using Python, Validation of the model results by Domain Experts, Build solution and operationalize.

Speaker Bio

Sunil Garg

Sunil Garg is the founder and CEO of dataVediK, an early stage startup specializing in Consulting, Big Data, Data Analytics, Machine Learning and end-to-end Data Ecosystems for Oil & Gas industry. Prior to this, he spent 20+ years establishing and growing Data Management, Big Data and Analytics businesses for Schlumberger. Sunil is a sought-after speaker at various industry conferences and also conducts Big Data, Machine Learning and Blockchain trainings for the Industry, the Government and the Academia.