---
title: "Andreas Lindholm, Fredrik Lindsten, Niklas Wahlström og Thomas B. Machine Learning"
ean: "9781108843607"
brand: "Andreas Lindholm, Fredrik Lindsten, Niklas Wahlström og Thomas B."
category: "Medier > Bøger"
price_min: 484
price_max: 484
currency: DKK
vendor_count: 1
in_stock: true
url: https://pricetracker.dk/p/9781108843607/machine-learning
last_checked: 2026-10-14
---

# Andreas Lindholm, Fredrik Lindsten, Niklas Wahlström og Thomas B. Machine Learning

EAN 9781108843607 · Mærke: Andreas Lindholm, Fredrik Lindsten, Niklas Wahlström og Thomas B. · Kategori: Medier > Bøger

Sammenlign priser på Andreas Lindholm, Fredrik Lindsten, Niklas Wahlström og Thomas B. Machine Learning fra 1 forhandler. Billigste pris nu: 484 kr hos Saxo DK. Se aktuelle priser og køb hos den billigste forhandler på https://pricetracker.dk/p/9781108843607/machine-learning

## Priser
- **Billigste pris nu:** 484 kr hos Saxo DK
- **Prisspænd:** 484 kr – 484 kr på tværs af 1 forhandler

## Forhandlere
| Forhandler | Pris | Levering |
|---|---|---|
| Saxo DK | 484 kr | — |

## Om produktet
Beskrivelse fra forhandleren Saxo DK:

> This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and logistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.

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Priserne er sidst kontrolleret 2026-10-14.