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  6. Practical R Chemistry Material Data Science (Learnable Alone)

Practical R Chemistry Material Data Science (Learnable Alone)

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last updated:Oct 30, 2023

CMC RESEARCH Ltd.
CMC RESEARCH Ltd.
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Focusing on "How to practically acquire machine learning and statistics?", this will be explained based on program examples in R language (approximately 75 scripts).

Book Title: (Learn Alone) Practical R Chemometrics and Material Data Science - Includes Appendix R Scripts - Publication Date: December 30, 2020 This text has been created to allow individuals to learn a series of steps including <1. Data Input>, <2. Data Shaping>, <3. Data Analysis>, and <4. Displaying and Outputting Analysis Results>, covering the installation of R and RStudio, the basics of programming, multivariate data analysis using feature representation (molecular descriptors) from chemical structures (regression and classification models through machine learning), and evaluation of validity and generalization performance. 【Features of this Book】 ➢ Written by members of the Bioinformatics Laboratory at Nara Institute of Science and Technology (Kanaya Laboratory). ➢ Includes freely usable R scripts created in the Kanaya Laboratory. ➢ Focuses on how to acquire machine learning and statistics, incorporating specific data from chemistry and materials chemistry, with explanations based on programming examples in R. ➢ Explained in accordance with four steps to utilize publicly available R packages. ➢ Edited to allow individuals to learn the entire process independently! A must-have book for every laboratory.

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(表紙画像)ひとりで学べる 実践Rケモ・マテリアル・データサイエンス.jpg

Practical R Chemistry Material Data Science (Learnable Alone)

(表紙画像)ひとりで学べる 実践Rケモ・マテリアル・データサイエンス.jpg
(表紙画像)ひとりで学べる 実践Rケモ・マテリアル・データサイエンス.jpg

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**Table of Contents** Chapter 1: Chemometrics, Materials, and Data Science Part I: Basics of Programming Chapter 2: How to Use RStudio Chapter 3: Introduction to R Programming Chapter 4: Data Structures Part II: Introduction to Data Mining Chapter 5: Statistical Testing Chapter 6: Creating Matrix Data Chapter 7: Unsupervised Learning: Visualization of Multivariate Data, Cluster Analysis, etc. Chapter 8: Multivariate Regression Models Chapter 9: Machine Learning Chapter 10: Processing Chemical Structures Part III: Practical Data Science with Scientific Data Chapter 11: Practical Solutions to Challenges in Chemistry and Materials Chemistry through Data Science Chapter 12: Conclusion: Further Developments *Regarding the Use of the Accompanying CD:* The accompanying CD contains a PDF of the book's content and a folder of R scripts developed by the Kanaya Lab. The R scripts are copyright-free, but the PDF of the book is protected by copyright, so its use is limited to the laboratory, department, or division that purchased it. Unauthorized reproduction or sharing is strictly prohibited.

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*Regarding the use of the accompanying CD: The accompanying CD contains a PDF of the book's content and a folder with R scripts developed by Kanaya Lab. The R scripts are copyright-free, but the PDF of the book is protected by copyright, so its use is limited to the research lab or department from which it was purchased. Unauthorized reproduction or sharing is strictly prohibited. *When applying, please download the order form from the PDF download. *For more details, please refer to the PDF materials or feel free to contact us.

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Book "Practical R for Chemometrics and Data Science (Learn on Your Own) - Includes R Scripts as Appendix -"

Book "Practical R for Chemometrics and Data Science (Learn on Your Own) - Includes R Scripts as Appendix -"

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We provide the latest industrial insights to our clients. By conducting market trend analysis, publishing technology‑related books and research reports, and organizing and managing seminars, we support research and development across a wide range of industries, with a primary focus on manufacturing. Our coverage spans diverse fields such as energy, batteries, chemicals, and biotechnology.

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