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    View Deep Learning Interview Questions by Shlomo KashaniPreview
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    Deep Learning Interview Questions

    by Shlomo Kashani

    This is the price your customers see. Edit price list

    Softcover
    Flexible laminated cover
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    About the Book

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    The book’s contents is a large inventory of numerous topics relevant to DL job interviews and graduate level exams. That places this work at the forefront of the growing trend in science to teach a core set of practical mathematical and computational skills. It is widely accepted that the training of every computer scientist must include the fundamental theorems of ML, and AI appears in the curriculum of nearly every university. This volume is designed as an excellent reference for graduates of such programs.
    Author website
    https://www.interviews.ai/
    Features & Details

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    • Primary Category: Medicine & Science
    • Additional Categories Computers & Internet
    • Project Option: 8×10 in, 20×25 cm
      # of Pages: 274
    • Isbn
      • Softcover: 9798349913914
    • Publish Date: May 02, 2025
    • Language English
    See More
    About the Creator
    shlomok
    Shlomo Kashani

    Shlomo Kashani is an AI scientist, strategic scholar, and visual artist. The founder of QNeura.ai, he has spent more than two decades designing production AI systems for technology companies and institutional clients worldwide. His work moves between disciplines that rarely share a page. He studied advanced signal processing at Queen Mary University of London (with distinction), quantum physics at Johns Hopkins University, and engineering at Ben-Gurion University. He is completing graduate studies in Defence and Strategic Studies at Missouri State University, examining how emerging technologies reshape political decision-making and the moral frameworks that govern state action under pressure. He is the author of Deep Learning Interviews and the recipient of a Gold Medal in the Kaggle AI Mathematical Olympiad. His paintings and essays explore perception, judgment, and the friction between technical systems and human experience.

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