Just Enough R!: An Interactive Approach to Machine Learning and Analytics
Autor Richard J. Roigeren Limba Engleză Hardback – 8 iun 2020
Features
- Gets you quickly using R as a problem-solving tool
- Uses RStudio’s integrated development environment
- Shows how to interface R with SQLite
- Includes examples using R’s Rattle graphical user interface
- Requires no prior knowledge of R, machine learning, or computer programming
- Offers over 50 scripts written in R, including several problem-solving templates that, with slight modification, can be used again and again
- Covers the most popular machine learning techniques, including ensemble-based methods and logistic regression
- Includes end-of-chapter exercises, many of which can be solved by modifying existing scripts
- Includes datasets from several areas, including business, health and medicine, and science
Richard J. Roiger is a professor emeritus at Minnesota State University, Mankato, where he taught and performed research in the Computer and Information Science Department for over 30 years.
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 222.43 lei 6-8 săpt. | |
CRC Press – 8 iun 2020 | 222.43 lei 6-8 săpt. | |
Hardback (1) | 743.74 lei 6-8 săpt. | |
CRC Press – 8 iun 2020 | 743.74 lei 6-8 săpt. |
Preț: 743.74 lei
Preț vechi: 1074.82 lei
-31% Nou
Puncte Express: 1116
Preț estimativ în valută:
142.34€ • 151.10$ • 118.60£
142.34€ • 151.10$ • 118.60£
Carte tipărită la comandă
Livrare economică 27 decembrie 24 - 10 ianuarie 25
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780367443207
ISBN-10: 0367443201
Pagini: 364
Ilustrații: 72
Dimensiuni: 178 x 254 x 21 mm
Greutate: 1.76 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
ISBN-10: 0367443201
Pagini: 364
Ilustrații: 72
Dimensiuni: 178 x 254 x 21 mm
Greutate: 1.76 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Cuprins
Preface. Acknowledgment. Author. Introduction to Machine Learning. Introduction to R. Data Structures and Manipulation. Preparing the Data. Supervised Statistical Techniques. Tree-Based Methods. Rule-Based Techniques. Neural Networks. Formal Evaluation Techniques. Support Vector Machines. Unsupervised Clustering Techniques. A Case Study in Predicting Treatment Outcome. Bibliography. Appendix A: Supplementary Materials and More Datasets. Appendix B: Statistics for Performance Evaluation. Subject Index. Index of R Functions. Script Index.
Notă biografică
Richard J. Roiger is a professor emeritus at Minnesota State University, Mankato where he taught and performed research in the Computer & Information Science Department for 27 years. Dr. Roiger’s Ph.D. degree is in Computer & Information Sciences from the University of Minnesota. Dr. Roiger continues to serve as a part-time faculty member teaching courses in data mining, artificial intelligence and research methods. Richard enjoys interacting with his grandchildren, traveling, writing and pursuing his musical talents.
Descriere
The main purpose of the text is to present the student with just enough of the R language, machine learning algorithms, and statistical methodology to set them on their way to a career in data science and machine learning.It is for a beginning course in machine learning, data mining & analytics, data science, or general data analysis.