Recommending a personalised product to the client is one of the crucial challenges for multiple businesses, including the top retailer from the UK. In this talk, we will walk through the world of Hadoop to discuss challenges and tools built by Data Scientists and ML Engineers to create stable, production-grade solutions for recommendations; then we will continue to consider the how different is world of the real-time serving in web-services.
micro.sphere.it #3: Data & AI
We invite you for next micro.sphere.it event!
Topic 1: How to recommend a personalised product to thousands of clients starting with raw data to real-time serving.
Bio:
Hubert Pomorski, Senior Big Data Developer at VirtusLab
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Topic 2: Lean AI – How to Implement a Production-Ready Deep Learning Model in Twelve Weeks
Many data science and machine learning projects fail which then cause high risks for companies. In product development, there is a concept though called “lean startup” which is all about minimizing risks. In this talk, I will present how lean concepts can be used for ML projects and how both of them are actually very related to each other. I will also present a project that we’re currently working on where we applied those ideas. And yes it’s a cool deep learning project.
Bio:
Dat Tran, Head of AI at Axel Springer
Dat’s interests are diverse from traditional machine learning, deep learning, AI in general to computer vision and NLP. He is a regular speaker and has presented at several renowned conferences. He also blogs about his work on Medium.
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