4 Takeaways from 'How Google Does Machine Learning' course

Today, Machine Learning (ML) technology is simplified and abstracted to an API call so you can solve a data-intensive pattern matching problem easily. Google's Move Mirror is a great example. While creating a standalone ML-based consumer app is reasonably straightforward, it can be quite challenging to infuse ML at scale into a mission-critical enterprise-class cloud platform. Enterprise apps have to consider various steps in the machine learning life cycle including data cleansing, integration, and production deployment. Operationalizing ML is a topic by itself and I'll share more on that in a future post.