Materials Data Science

Language: English

Published by Springer, Springer Mai 2025, 2025

3031465679 / 9783031465673

Series: Book 4 of 4 - The Materials Research Society

  • Softcover
  • New
See all details

Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

5-star seller

AbeBooks seller since January 23, 2017

Softcover

Condition: New

US$ 80.32

US$ 67.28 shipping 
Ships from Germany to U.S.A.

Quantity: 1 available

Add to basket
Free 30-day returns

Item description from seller

This item is printed on demand - Print on Demand Titel. Neuware -This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications. Almost all methods and algorithms introduced are implemented 'from scratch' using Python and NumPy.The book starts with an introduction to statistics and probabilities, explaining important concepts such as random variables and probability distributions, Bayes' theorem and correlations, sampling techniques, and exploratory data analysis, and puts them in the context of materials science and engineering. Therefore, it serves as a valuable primer for both undergraduate and graduate students, as well as a review for research scientists and practicing engineers.The second part provides an in-depth introduction of (statistical) machine learning. It begins with outlining fundamental concepts and proceeds to explore a variety of supervised learning techniques for regression and classification, including advanced methods such as kernel regression and support vector machines. The section on unsupervised learning emphasizes principal component analysis, and also covers manifold learning (t-SNE and UMAP) and clustering techniques. Additionally, feature engineering, feature importance, and cross-validation are introduced.The final part on neural networks and deep learning aims to promote an understanding of these methods and dispel misconceptions that they are a 'black box'. The complexity gradually increases until fully connected networks can be implemented. Advanced techniques and network architectures, including GANs, are implemented 'from scratch' using Python and NumPy, which facilitates a comprehensive understanding of all the details and enables the user to conduct their own experiments in Deep Learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 644 pp. Englisch.…

Seller Inventory # 9783031465673

Title
Materials Data Science
Author
Stefan Sandfeld
Publisher
Springer, Springer Mai 2025
Publication year
2025
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3031465679
ISBN 13
9783031465673
Item weight
961 grams
Dimensions
235x155x35 mm
Series
Book 4 of 4: The Materials Research Society

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

5-star seller

AbeBooks seller since January 23, 2017

Shipping rates from Germany to U.S.A.

Item60 to 60 business days60 to 60 business days
First itemUS$ 67.28US$ 84.10
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

  • Visa
  • Mastercard
  • American Express
  • Apple Pay
  • Google Pay
  • Check
  • Paypal

Store description

Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur

Specialty

Modernes Antiquariat - Bücher von 1960 bis heute

Seller's business information

buchversandmimpf2000

Germany