Emerging Battery Technologies to Boost the Clean Energy Transition
Stefano Passerini, Linda Barelli, Manuel Baumann, Jens Peters, Marcel Weil
Inbunden, 2024
719 kr
Del i serien Materials Research Society Series
Materials Data Science
Introduction to Data Mining, Machine Learning, and Data-Driven Predictions for Materials Science and Engineering
Inbunden, Engelska, 2024
1 289 kr
Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
Finns i fler format (1)
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.
Produktinformation
- Utgivningsdatum2024-05-09
- Mått155 x 235 x 37 mm
- Vikt1 176 g
- FormatInbunden
- SpråkEngelska
- SerieMaterials Research Society Series
- Antal sidor618
- FörlagSpringer International Publishing AG
- ISBN9783031465642
Tillhör följande kategorier
Hoppa över listan
Mer från samma serie
Emerging Battery Technologies to Boost the Clean Energy Transition
Stefano Passerini, Linda Barelli, Manuel Baumann, Jens Peters, Marcel Weil
Häftad, 2024
579 kr
Gallium Nitride and Related Materials
Isik C. Kizilyalli, Jung Han, James S. Speck, Eric P. Carlson
Inbunden, 2025
1 859 kr
Gallium Nitride and Related Materials
Isik C. Kizilyalli, Jung Han, James S. Speck, Eric P. Carlson
Häftad, 2026
1 859 kr
Transition Metal-Based Layered Double Hydroxides
Chaudhery Mustansar Hussain, Krishna Gopal Bhattacharyya, Shadpour Mallakpour, Priyadarshi Roy Chowdhury, Himani Medhi
Inbunden, 2026
3 139 kr
Creation of Materials by Super-Thermal Field in Additive Manufacturing
Yuichiro Koizumi, Takayoshi Nakano, Yoshitaka Adachi, Kohei Morishita, Kazuhisa Sato, Yoshiaki Toda, Takuya Ishimoto, Teiichi Kimura, Eric Jägle, Albert C. To
Inbunden, 2027
3 889 kr
Hoppa över listan
Du kanske också är intresserad av
- Nyhet
Del 3
Interface Ionics
Yasutoshi Iriyama, Koji Amezawa, Yoshitaka Tateyama, Naoaki Yabuuchi
Häftad, 2025
3 569 kr
Creation of Materials by Super-Thermal Field in Additive Manufacturing
Yuichiro Koizumi, Takayoshi Nakano, Yoshitaka Adachi, Kohei Morishita, Kazuhisa Sato, Yoshiaki Toda, Takuya Ishimoto, Teiichi Kimura, Eric Jägle, Albert C. To
Inbunden, 2027
3 889 kr
Interface Ionics
Yasutoshi Iriyama, Koji Amezawa, Yoshitaka Tateyama, Naoaki Yabuuchi
Inbunden, 2024
3 569 kr