Data Science and Machine Learning for Non-Programmers
Using SAS Enterprise Miner
Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series;
- Publisher's listprice GBP 44.99
-
21 493 Ft (20 470 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 2 149 Ft off)
- Discounted price 19 344 Ft (18 423 Ft + 5% VAT)
Subcribe now and take benefit of a favourable price.
Subscribe
21 493 Ft
Availability
Not yet published.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher Chapman and Hall
- Date of Publication 1 January 2026
- ISBN 9780367751968
- Binding Paperback
- No. of pages589 pages
- Size 254x178 mm
- Language English
- Illustrations 419 Illustrations, color; 419 Line drawings, color; 143 Tables, black & white 700
Categories
Short description:
As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming
MoreLong description:
As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively.
Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders.
Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.
MoreTable of Contents:
Part I: Introduction to Data Mining. 1. Introduction to Data Mining and Data Science. 2. Data Mining Processes, Methods, and Software. 3. Data Sampling and Partitioning. 4. Data Visualization and Exploration. 5. Data Modification. Part II: Data Mining Methods. 6. Model Evaluation. 7. Regression Methods. 8. Decision Trees. 9. Neural Networks. 10. Ensemble Modeling. 11. Presenting Results and Writing Data Mining Reports. 12. Principal Component Analysis. 13. Cluster Analysis. Part III: Advanced Data Mining Methods. 14. Random Forest. 15. Gradient Boosting. 16. Bayesian Networks.
More
