lindholm andreas (17 Ergebnisse)

hardcover. Zustand: Very Good. Cover and edges may have some wear.

Hardcover. Zustand: Like New. First Edition. Hardback book in nearly new condition: firm and square with strong joints. Just a few hardly noticeable rubs or very mild bumps. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: Used. pp. 350.

Zustand: Used. pp. 350.

Zustand: New. In.

Zustand: New. 2022. New. Hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 325 pages. 10.20x7.20x0.80 inches. In Stock.

Zustand: New. This coherent introduction to machine learning for readers with a background in basic linear algebra, statistics, probability, and programming is suitable for advanced BSc or MSc courses. It covers theory and practice of basic and advanced methods such as d.

Buch. Zustand: Neu. Neuware -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.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 338 pp. Englisch.

Buch. Zustand: Neu. Machine Learning | A First Course for Engineers and Scientists | Andreas Lindholm (u. a.) | Buch | Gebunden | Englisch | 2022 | Cambridge University Pr. | EAN 9781108843607 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Buch. Zustand: Neu. Neuware - 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.

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9781856692526.

Buch. Zustand: Neu. Neuware -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. 338 pp. Englisch.

Två volymer. Förlagets halvlinneband, tryckta skyddsomslag i färg (aningen nötta). Gott skick. Stockholm, Tidens förlag, 1943-44. 8:o. 288; + 378 s. Illustrerade. Med litteraturförteckning. Innehåller bl. a.: "De obesuttna", "Städernas arbetare", "Brukens arbetare", "Böndernas tjänstefolk", "Herrgårdsbornas och stadsfolkets tjänstefolk", "Torpare", "Statare", "Städernas arbetare", "Brukens arbetare", "Tillfälliga bostäder", "Arbetsdräkt", "Kosthåll", "Arbetsvandringar", "Landsbygden", "I staden", "Städerna", "Avlöningsformer", "Festseder och fritidssysslor", "Arbetets folkdiktning", "Arbetaren och språket".

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9781856692526.