Apres acceptation de la commande, le delai moyen d'expedition depuis le Japon est de 48 heures. Le delai moyen de livraison est de 3 a 4 semaines. En cas de circonstances exceptionnelles, les delais peuvent s'etendre jusqu'à 2 mois.

Voir le détail de l'annonce

Vous avez choisi le retrait chez le vendeur à

Payez directement sur Rakuten (CB, PayPal, 4xCB...)
Récupérez le produit directement chez le vendeur
Rakuten vous rembourse en cas de problème

Terminer ma commande

Gratuit et sans engagement

Félicitations !

Nous sommes heureux de vous compter parmi nos membres du Club Rakuten !

TROUVER UN MAGASIN

Adresse

Retour

Horaires

Note :

Avis sur Machine Learning With Python de Zollanvari, Amin Format Broché - Livre Informatique

Note : 0 0 avis sur Machine Learning With Python de Zollanvari, Amin Format Broché - Livre Informatique

Donnez votre avis

Donnez votre avis sur ce produit

Votre note * : 1/5 2/5 3/5 4/5 5/5 Veuillez donner une note au produit

Le titre de votre avis* : Saisissez un titre

Quelques conseils :

Donnez le ton de votre avis, résumez-le en quelques mots qui apparaîtront comme le titre de votre avis.

Votre avis* : (40 caractères minimum) Saisissez un avis

Quelques conseils :

N'hésitez pas à mettre en avant les caractéristiques de ce produit, n'oubliez pas de mentionner ses avantages et/ou ses défauts éventuels. Décrivez précisément, argumentez, soyez convaincant !

Annuler

Les avis publiés font l'objet d'un contrôle automatisé de Rakuten.

Produits similaires

Présentation Machine Learning With Python de Zollanvari, Amin Format Broché
- Livre Informatique

Livre Informatique - Zollanvari, Amin - 01/07/2024 - Broché - Langue : Anglais

Auteur(s) : Zollanvari, Amin

Editeur : Springer International Publishing Ag

Langue : Anglais

Parution : 01/07/2024

Format : Moyen, de 350g à 1kg

Nombre de pages : 472

Dimensions : 23.5 x 15.5 x 2.6

ISBN : 3031333446

Résumé :
This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made based on one criterion: whether the practical utility of a certain method justifies its theoretical elaboration for students with a typical mathematical background in engineering and other quantitative fields. As a result, not only does the book contain practically useful techniques, it also presents them in a mathematical language that is accessible to both graduate and advanced undergraduate students.

The textbook covers a range of topics including nearest neighbors, linear models, decision trees, ensemble learning, model evaluation and selection, dimensionality reduction, assembling various learning stages, clustering, and deep learning along with an introduction to fundamental Python packages for data science and machine learning such as NumPy, Pandas, Matplotlib, Scikit-Learn, XGBoost, and Keras with TensorFlow backend.

Given the current dominant role of the Python programming language for machine learning, the book complements the theoretical presentation of each technique by its Python implementation. In this regard, two chapters are devoted to cover necessary Python programming skills. This feature makes the book self-sufficient for students with different programming backgrounds and is in sharp contrast with other books in the field that assume readers have prior Python programming experience. As such, the systematic structure of the book, along with the many examples and exercises presented, will help the readers to better grasp the content and be equipped with the practical skills required in day-to-day machine learning applications.

...

Biographie:
Amin Zollanvari is an Associate Professor of Electrical and Computer Engineering and the Head of Data Science Laboratory at Nazarbayev University. He received his B.Sc. and M.Sc. degrees in electrical engineering from Shiraz University, Iran, in 2003 and 2006, respectively, and a Ph.D. in electrical engineering from Texas A&M University, in 2010. He held a postdoctoral position at Harvard Medical School and Brigham and Women's Hospital, Boston MA (2010-2012), and later joined the Department of Statistics at Texas A&M University as an Assistant Research Scientist (2012-2014). He has taught a number of courses on machine learning, programming, and statistical signal processing both at graduate and undergraduate level and has authored over 80 research papers in prestigious journals and international conferences on fundamental and practical machine learning and pattern recognition. He is currently an IEEE Senior member and has served as an Associate Editor of IEEE Access since 2018....

Sommaire:
This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made based on one criterion: whether the practical utility of a certain method justifies its theoretical elaboration for students with a typical mathematical background in engineering and other quantitative fields. As a result, not only does the book contain practically useful techniques, it also presents them in a mathematical language that is accessible to both graduate and advanced undergraduate students.

...

Détails de conformité du produit

Consulter les détails de conformité de ce produit (

Personne responsable dans l'UE

)

Machine Learning with Python - Zollanvari, Amin

Avis sur Machine Learning With Python de Zollanvari, Amin Format Broché - Livre Informatique

Présentation Machine Learning With Python de Zollanvari, Amin Format Broché - Livre Informatique

Présentation Machine Learning With Python de Zollanvari, Amin Format Broché
- Livre Informatique