Driven by Data | The Podcast
Kyle Winterbottom was joined by Sami Rahman, Head of Data Engineering and Data Platform at Penguin Random House. Where we discuss how to build an MLOps capability that drives business benefits
Within this episode, we cover…
🎤His journey from Business Psychologist to “MI5 reject” to Data Leader
🎤Being told to give up because he would never work in data without a computer science degree
🎤Being unemployed for 1 year and receiving 326 rejections
🎤Building an entire MLOps system for £50,000
🎤Reducing the time to build models from months to days
🎤Reducing the time to productionise ML models from 5 months to minutes
🎤Generating a 200% increase in performance across all 12 measures of success
🎤Why MLOps forces you to think about how the model will drive value
🎤How MLOps can be beneficial across the whole D&A value chain
🎤The differences between MLOps and AIOps
🎤Why MLOps isn’t new DevOps
🎤The future of MLOps and the relationship with Genertaive AI
🎤Choosing the right MLOps tech and tooling
🎤Why you need to explain MLOps in less than 2 sentences
🎤When you should start your MLOps journey
🎤The usual pitfalls both technical and business that people should be aware of
🎤The ethical considerations
🎤AI Explainability – how to understand the outcomes in a business context
🎤Why we should build an “evil” AI to tackle bias
🎤The skills you need to execute successful MLOps
