Oil and Gas enterprises today want to accelerate innovation by building data and machine learning into their business. Machine Learning has become essential for use cases such as predictive maintenance, efficient drilling operations and supply chain optimization. However, most companies struggle with ingesting and preparing large diverse datasets for analytics, managing the proliferation of ML frameworks, and moving models in development to production.
In this Oil and Gas focused workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Delta Lake, the de facto data lake framework in enterprises today, to unify data at massive scale across various sources from well logs to drilling reports, geospatial data and more. You’ll learn how to use ML frameworks (i.e. TensorFlow, XGBoost, Scikit-Learn, etc.) to train models based on different requirements. And finally, you can learn how to use MLflow to track experiment runs between multiple users within a reproducible environment, and manage the deployment of models to production.
Join this half-day workshop to learn how unified data analytics can bring data science, business analytics and engineering together to accelerate your data and ML efforts. This free workshop will give you the opportunity to:
- Learn how Shell, Devon Energy, Halliburton and other oil and gas customers are using Data and ML
- Learn about the latest ML use cases in the Oil and Gas industry including predictive maintenance, improved drilling efficiency and supply chain optimization
- Learn how to build highly scalable and reliable pipelines to ingest, process, and organize massive data sets from a variety of sources in order to train hundreds of ML models to improve operations and discovery
- Get deeper insight into Apache Spark™ and Databricks, including the latest updates with Delta Lake
We will use Zoom for a virtual meeting environment. Your Zoom link will be sent to you upon registration.
We look forward to seeing you on September 16th!