Adopt Machine Learning at Scale with MLOps Workshop

Digital Native Business Tech Workshop: Episode 3 From retail to financial services, machine learning (ML) has evolved to be a part of the average daily user experience. However, most organizations underestimate the complexity of their ML development lifecycle and are often left clueless on how to properly manage their ML projects. The average ML development lifecycle consists of 4 main stages: model development, model deployment, model operations, and model retraining. When each stage has their own specific needs and requirements, it’s no wonder that managing the ML lifecycle is an operational challenge. Fortunately, Machine Learning Operations (MLOps) was created to accelerate ML adoption by simplifying the development lifecycle. Join the third episode of our Digital Native Business Tech Talks to hear from Oracle Senior Solution Specialist, DevOps – Wei How Owi and learn how you can adopt ML at scale with MLOps using Oracle Cloud Infrastructure (OCI) Cloud-Native services. Sign up for the upcoming workshop - Application Modernization Strategies: Increase Agility and Innovate with Cloud Native Technologies Join Stephane Moriceau, OCI Solutions Director from Oracle and guest speaker Subrat Gaur, GM, Consumer Domain and Consulting from Wipro as they explore how enterprises are modernizing applications leveraging cloud-based managed services to generate better outcomes for their businesses. Register for Application Modernization Strategies: Increase Agility and Innovate with Cloud Native Technologies: https://bit.ly/AccelerateOutcome Catch up on the previous episodes of our Digital Native Business Executive Tech Talks: Episode 1: Scale fast, reduce cost, build rapidly with Next Gen cloud: https://bit.ly/3fRtq3X Episode 2: Accelerating your adoption of a Cloud-Native Infrastructure: https://bit.ly/3rkXveE