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The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning Derived from Millions of Data Science Workflows

Published: 13 August 2016 Publication History

Abstract

With hundreds of thousands of users, RapidMiner is the most frequently used visual workflow platform for machine learning. It covers the full spectrum of analytics from data preparation to machine learning and model validation. In this presentation, I will take you on a tour of machine learning which spans the last 15 years of research and industry applications and share key insights with you about how data scientists perform their daily analysis tasks. These patterns are extracted from mining millions of analytical workflows that have been created with RapidMiner over the past years. This talk will address important questions around the data mining process such as: What are the most frequently used solutions for typical data quality problems? How often are analysts using decision trees or neural networks? And does this behavior change over time or depend on the users experience level?

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MP4 File (kdd2016_mierswa_best_practices_01-acm.mp4)

Cited By

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  • (2020)Using very‐high‐resolution satellite imagery and deep learning to detect and count African elephants in heterogeneous landscapesRemote Sensing in Ecology and Conservation10.1002/rse2.1957:3(369-381)Online publication date: 23-Dec-2020

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  1. The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning Derived from Millions of Data Science Workflows

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    Published In

    cover image ACM Conferences
    KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
    August 2016
    2176 pages
    ISBN:9781450342322
    DOI:10.1145/2939672
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 August 2016

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    Author Tags

    1. analytics
    2. data visualization
    3. machine learning tools
    4. visual workflow
    5. wisdom of the crowds

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    KDD '16 Paper Acceptance Rate 66 of 1,115 submissions, 6%;
    Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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    • (2020)Using very‐high‐resolution satellite imagery and deep learning to detect and count African elephants in heterogeneous landscapesRemote Sensing in Ecology and Conservation10.1002/rse2.1957:3(369-381)Online publication date: 23-Dec-2020

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