Ganesh has 22 years of progressive experience in building disparate software systems on a variety of technology stack & managing distributed technology teams for some of the Fortune 500 companies. He holds a Masters in Chemical Engineering from Indian Institute of Science [IISc], Bangalore, India. Ganesh is presently the Senior Director of Machine Learning Engineering & Operations at S&P Global Market Intelligence building essential intelligence and insights for customers, driving business outcomes by applying advanced Analytics & Data Science. A committed lifelong learner, a tech blog writer and a podcast speaker and he shares his knowledge through Coaching and Mentoring.
The delivery of Machine learning solutions should reconcile various objectives. Deploying Machine Learning to Production requires integrated discipline and practice across data science & development teams. MLOps provides guidelines and best practices to be followed by data scientists, software engineers & project managers and fosters a culture in which ML technologies can generate business benefits by rapidly building, testing and releasing ML models in to production. The talk succinctly summarizes the challenges in implementing MLOps and introduces the core MLOps drivers that eventually lays the foundation blocks of a Analytics Platform. The talk highlights the steps needed to build a generic purpose Analytics Platform conforming to the stages in Machine Learning development projects and finally touches upon a mini case study carried out by S&P Global’s Market Intelligence Product and Data Science Team.
