Da: Goodbooks Company, Springdale, AR, U.S.A.
Condizione: good. Has a sturdy binding with some shelf wear. May have some markings or highlighting. Used copies may not include access codes or Cd's. Slight bending may be present.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Da: Lakeside Books, Benton Harbor, MI, U.S.A.
EUR 48,06
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
EUR 53,17
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Most intermediate-level machine learning books usually focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance and the need to be able to explain why and how your ML model makes the predictions that it does. This practical guide brings together the best-in-class techniques for model interpretability and explains model predictions in a hands-on approach. Experienced ML practitioners will be able to more easily apply these tools in their daily workflow.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Da: California Books, Miami, FL, U.S.A.
EUR 58,49
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
EUR 65,37
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Most intermediate-level machine learning books usually focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance and the need to be able to explain why and how your ML model makes the predictions that it does. This practical guide brings together the best-in-class techniques for model interpretability and explains model predictions in a hands-on approach. Experienced ML practitioners will be able to more easily apply these tools in their daily workflow.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 50,82
Quantità: 19 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 58,46
Quantità: 19 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Revaluation Books, Exeter, Regno Unito
EUR 76,84
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 350 pages. 9.19x7.00x0.80 inches. In Stock.
Da: Majestic Books, Hounslow, Regno Unito
EUR 84,10
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
EUR 55,33
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Most intermediate-level machine learning books usually focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance and the need to be able to explain why and how your ML model makes the predictions that it does. This practical guide brings together the best-in-class techniques for model interpretability and explains model predictions in a hands-on approach. Experienced ML practitioners will be able to more easily apply these tools in their daily workflow.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New.
Da: moluna, Greven, Germania
EUR 59,94
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Über den AutorMichael Munn is a research software engineer at Google. His work focuses on better understanding the mathematical foundations of machine learning and how those insights can be used to improve machine learning models at.
EUR 61,11
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Most intermediate-level machine learning books usually focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance and the need to be able to explain why and how your ML model makes the predictions that it does. This practical guide brings together the best-in-class techniques for model interpretability and explains model predictions in a hands-on approach. Experienced ML practitioners will be able to more easily apply these tools in their daily workflow.