Speaker

Let us face the facts, startups don't have the money like tech giants. So, having a dedicated ML engineering team is completely out of the box. This is a story of difficulties I faced during the first few years of my career and how I overcome those. This is not much of a technical talk. If you want to hear about deep learning architecture or how I came to some aha moment because I am able to achieve higher accuracy than existing state of the art models, or how ml can help solve estimating climate change, then this talk is not for you. This is more casual tongue in cheek story of problems I encountered for past few years, pivot from struggling to build generalised ai to business impact oriented problems.