Deudas técnicas y ocultas en el aprendizaje automático #ML: un análisis de ingenieros de #Google


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RxRegistration ID
R0Hash MD5 (of R3):2ec2747767ec2abc671f85e41b8f19bb
R1Registration number (in the domain editorialia.com at WordPress):dmeditorialiawp.6113
R2Date-p-order (ddmmyyyypx):18032020p1
R3Cid (combined id R1+R2):dmeditorialiawp.611318032020p1
R4Resource official title:Hidden Technical Debt in Machine Learning Systems
R5Publisher:NIPS
R7Resource website (2) (Editorial|company):papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems
R8Collection (wich resource belongs):Advances in Neural Information Processing Systems 28 (NIPS 2015)
R12Authors (separated by commas):D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-François Crespo, Dan Dennison
R14Keyword (selected 1 among the labels applied to this entry):=machinelearning
R15QR code (of the linked url at WP):qr code
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