Autor: | Miroslav Kubat |
Lehekülgede arv: | 458 |
Ilmumisaasta: | 2021 |
Kauba ID: | 18245114 |
This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches that have become highly topical, including deep learning, and auto-encoding, introductory information about temporal learning and hidden Markov models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and pictures, and with a lot of practical advice and discussions of simple applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, rule-induction programs, artificial neural networks, support vector machines, boosting algorithms, unsupervised learning (including Kohonen networks and auto-encoding), deep learning, reinforcement learning, temporal learning (including long short-term memory), hidden Markov models, and the genetic algorithm. Special attention is devoted to performance evaluation, statistical assessment, and to many practical issues ranging from feature selection and feature construction to bias, context, multi-label domains, and the problem of imbalanced classes.
Kauba ID: | 18245114 |
Kategooria: | Majandusalased raamatud |
Tootepakendite arv: | 1 tk. |
Paki suurus ja kaal (1): | 0,3 x 0,3 x 0,1 m, 0,2 kg |
Kirjastus: | Springer Nature Switzerland AG |
Raamatu keel: | Inglise keel |
Tüüp: | Täpsustamata |
Autor: | Miroslav Kubat |
Lehekülgede arv: | 458 |
Ilmumisaasta: | 2021 |
Toodete pildid on illustratiivsed ja näitlikud. Tootekirjelduses sisalduvad videolingid on ainult informatiivsetel eesmärkidel, seega võib neis sisalduv teave erineda tootest endast. Värvid, märkused, parameetrid, mõõtmed, suurused, funktsioonid, ja / või originaaltoodete muud omadused võivad nende tegelikust väljanägemisest erineda, seega palun tutvuge tootekirjeldustes toodud tootespetsifikatsioonidega.