Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent

Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent

Zhou, Jianlong
Chen, Fang

Paperback

Series: Human-Computer Interaction

General Computers

ISBN10: 3030080072
ISBN13: 9783030080075
Publisher: Springer Nature
Published: Jan 10 2019
Pages: 482
Weight: 1.55
Height: 1.02 Width: 6.14 Depth: 9.21
Language: English

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of black-box in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications.

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