Practical machine learning illustrated with KNIME / (Record no. 141389)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01672nam a22002537a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260710173057.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260710s2024 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789819739530 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | PK-LaUMT |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Item number | PRA- |
| 245 00 - TITLE STATEMENT | |
| Title | Practical machine learning illustrated with KNIME / |
| Statement of responsibility, etc | Yu Geng . . . [et al.] |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Cham : |
| Name of publisher, distributor, etc | Springer, |
| Date of publication, distribution, etc | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xiv, 304 p. |
| 500 ## - GENERAL NOTE | |
| General note | Includes bibliographical references. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book guides professionals and students from various backgrounds to use machine learning in their own fields with low-code platform KNIME and without coding. Many people from various industries need use machine learning to solve problems in their own domains. However, machine learning is often viewed as the domain of programmers, especially for those who are familiar with Python. It is too hard for people from different backgrounds to learn Python to use machine learning. KNIME, the low-code platform, comes to help. KNIME helps people use machine learning in an intuitive environment, enabling everyone to focus on what to do instead of how to do. This book helps the readers gain an intuitive understanding of the basic concepts of machine learning through illustrations to practice machine learning in their respective fields. The author provides a practical guide on how to participate in Kaggle completions with KNIME to practice machine learning techniques |
| 546 ## - LANGUAGE NOTE | |
| Language note | Eng |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | KNIME-(computer system) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Geng, Yu |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Li, Qin |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Yang, Geng |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Qiu, Wan |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Home library | Current library | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|
| UMT Main Campus | UMT Main Campus | 2026-07-10 | 006.31 PRA- | 153278 | 2026-07-10 | 2026-07-10 | Books |