Machine learning for designers / (Record no. 91181)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 01796nam a22001817a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 231125b2016 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789355422880 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 HEB-P |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Hebron, Patrick |
| 245 ## - TITLE STATEMENT | |
| Title | Machine learning for designers / |
| Statement of responsibility, etc. | Patrick Hebron |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | India |
| Name of publisher, distributor, etc. | Shroff Publishers |
| Date of publication, distribution, etc. | 2016 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 71p. |
| 500 ## - GENERAL NOTE | |
| General note | Machine learning is no longer just a tool for data scientists. By taking advantage of recent advances in this technology, UI and UX designers can find ways to better engage with and understand their users. This O'Reilly report not only introduces you to contemporary machine learning systems, but also provides a conceptual framework to help you integrate machine-learning capabilities into your user-facing designs. Using tangible, real-world examples, author Patrick Hebron explains how machine-learning applications can affect the way you design websites, mobile applications, and other software. You'll learn how recent advancements in machine learning can radically enhance software capabilities through natural language processing, image recognition, content personalization, and behavior prediction. This report explains how to: Leverage machine-generated user insights to provide a more personalized customer or user experience Spot opportunities for the integration of machine-learning capabilities into existing designs and platforms Choose the right machine-learning platforms or services Design for the probabilistic and often imprecise nature of machine-generated data Stay up to date with advancements in the field and spot emerging opportunities for machine learning-aided design |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | User interfaces (Computer systems) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Streaming video |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Internet videos |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | 003-007 | BITS Pilani Hyderabad | BITS Pilani Hyderabad | General Stack (For lending) | 25/11/2023 | 006.31 HEB-P | 47540 | 13/07/2024 | 25/11/2023 | Books |