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CS Colloquium: Learning-Based Methods for Automating Exploratory Data Analysis by Amit Somech, TAU
June 2 @ 12:00 pm - 1:00 pm IDT
Amit Somech from tell Aviv University.
The lecture will be given in zoom
zoom link: https://zoom.us/j4595130079
Thursday noon 12:00
Title: Learning-Based Methods for Automating Exploratory Data Analysis
Exploratory Data Analysis (EDA) is an integral part of the data-science pipeline, in which users interactively explore datasets by issuing a sequence of analysis operations (e.g. filter, aggregation, and visualization).
EDA is known as a difficult task that requires profound analytical skills, experience, and familiarity with the data domain.
In this talk we introduce the problem of automating the EDA process, which has the potential of reducing the human effort in analyzing and understanding arbitrary datasets.
We present the major computational challenges that stem from the problem, then review several learning-based solutions: starting from a recommender system that suggests a single exploratory step, then a kNN-based classifier for dynamically predicting “interestingness” preferences, and finally, we show how an entire EDA notebook can be produced using deep reinforcement learning.
We conclude the talk with a discussion on the remaining open questions, and a brief review of selected ongoing and future works.
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