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This virtual meetup starts at 10 am in San Francisco, 1 pm in the East Coast, 6 pm in London, 10:30 pm Bangalore, India (Time zone converter -
Use the following link for the live event on YouTube:
Abstract: The recently open-sourced platform called Marvin AI is helping B2W Digital data science teams to put some interesting projects into production, such as dynamic pricing and fraud detection.
The platform is helping B2W avoid challenges that are common in machine learning projects, like building a hypothesis prototype and putting it in production, enabling it to handle ever-increasing data sets, and supporting the necessary throughput of the largest e-commerce company in South America.
Marvin AI is made up of tools, libraries, an embedded server that exposes microservices to serve and manage models, and a very useful design pattern, DASFE, that simplifies the process of building new machine learning engines.
In this 90-minute hands-on tutorial, one of the project architects and main open source contributor will explain all the core features of Marvin.
Speaker: Daniel Takabayashi
Daniel is a machine learning manager at B2W Digital. He is passionate about disruptive technology. He has an extensive experience in enterprise architectural projects, as well as solutions for BigData (Eg. Hadoop and spark) and Machine Learning in large scale (Eg. Mahout, Spark and Graphlab).