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Spark+AI Summit 2020: Notes cover feature engineering, data quality, and model efficiency

By PulseAugur Editorial · [2 sources] ·

Eugene Yan's notes from the Spark+AI Summit 2020 cover practical applications and agnostic talks in deep learning and data engineering. Application-specific sessions highlighted frameworks like Airbnb's Zipline for feature engineering and Sputnik for data engineering, alongside Gojek's Feast and Netflix's data quality approaches. The agnostic talks focused on improving deep learning efficiency through techniques such as model pruning, quantization, and distillation, with examples from IBM and Instagram. AI

RANK_REASON The content consists of notes and summaries of talks from a summit, focusing on research and engineering practices rather than a new release or major industry event.

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AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Spark+AI Summit 2020: Notes cover feature engineering, data quality, and model efficiency

COVERAGE [2]

  1. Eugene Yan TIER_1 English(EN) ·

    My Notes From Spark+AI Summit 2020 (Application-Specific Talks)

    Part II of the previous write-up, this time on applications and frameworks of Spark in production

  2. Eugene Yan TIER_1 English(EN) ·

    My Notes From Spark+AI Summit 2020 (Application-Agnostic Talks)

    Sharing my notes & practical knowledge from the conference for people who don't have the time.

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