Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeUnlocking Healthcare Potential with Synthetic Data: The Role of IBM WatsonX.aiCo-authored by Caroline Scanlan, Rakshith Dasenahalli Lingaraju and Richard Williams.Aug 30Aug 30
Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeLeveraging Generative AI in Genomics with IBM’s watsonx PlatformCo-authored by Rakshith Dasenahalli Lingaraju and Richard Williams.Jun 10Jun 10
Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeRevolutionizing RFP Management in Healthcare and Life Sciences using IBM watsonxCo-authored by Caroline Scanlan, and Rakshith Dasenahalli Lingaraju.Jun 7Jun 7
Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeTechniques for explanation retrieval with Watson OpenScaleCo-authored by Courtney Branson, and Rakshith Dasenahalli Lingaraju.Oct 26, 2022Oct 26, 2022
Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeMachine learning model replacement in complex and agile micro services architecturesThis article provides an insider view on managing complex ML model deployments from the lens of operational excellence, challenges and…Oct 3, 2022Oct 3, 2022
Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeConcurrent load testing for ML models deployed in Cloud Pak using LocustBefore enterprises decide to productionalize a Machine Learning model and make it available for online consumption, the model undergoes…Oct 3, 2022Oct 3, 2022
Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeRapid scaling and deployment of machine learning models in mission critical systemsOne of the main issues in MLOps(machine learning operations) is how to manage and maintain various KPIs of productionized ML model (API)…Oct 3, 2022Oct 3, 2022
Rakshith Dasenahalli LingarajuinIBM Data Science in PracticeDeploying a Model in a Hybrid Cloud StrategyChoosing the best cloud solution for highly sensitive, heavily regulated data with models that might need to be consumed by the public.Dec 28, 2019Dec 28, 2019