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Is it time to unite? Leverage Mars to bridge data science and machine learning Офлайн 2021

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Тезисы

Mars is an open-source project which aims at accelerating data science tools like numpy, pandas, scikit-learn and so forth with technology of parallelism and distributed systems. Data scientist or engineer would be able to make slight modification on the old code to migrate to Mars in order to accelerate their tasks. Machine learning tasks could also leverage Mars to accelerate the data manipulation and processing as well.

This talk would talk about the current workflows for data science and machine learning, how Mars could play a role to unite and accelerate the current workflows. The implementation behind would be mentioned as well.

Xuye Qin
Alibaba

I am a senior software engineer from Alibaba Group Company, Python enthusiast. working on combining big data with Python language.
Currently, as the architect and core developer, I am leading an open-source project Mars which is a tensor-based unified framework for large-scale data processing, Mars extends numpy ability with parallel and distributed computing, and in the long term, Mars aims to create the distributed counterparts of scipy stack which will not be subject to the ability of a single machine. I also worked on a project named PyODPS that users can write pandas-like DataFrame which can be compiled into SQL on the big data platforms.
When I was a student, I developed a distributed crawling framework named cola.