| 000 | 01173nam a22002417a 4500 | ||
|---|---|---|---|
| 008 | 220615b |||||||| |||| 00| 0 eng d | ||
| 020 | _a9780367861575 | ||
| 082 |
_a371.100285 _bVER |
||
| 100 | _aVerma, Dinesh C | ||
| 245 | _aFederated AI for Real- World Business Scenarios | ||
| 260 |
_aBoca Ratio: _bCRC Press: _c2021. |
||
| 300 | _a205p. | ||
| 365 |
_aUKP _b125.00 _d13238.00 |
||
| 440 | _aA Science Publishers Book | ||
| 500 | _aContents: Chapter 1. Introduction to Artificial Intelligence. 2. Scenarios for Federated AI. 3. Naive Federated Learning Approaches. 4. Addressing Data Mismatch Issues in Federated AI. 5. Addressing Data Skew Issues in Federated Learning. 6. Addressing Trust Issues in Federated Learning. 7. Addressing Synchronization Issues in Federated Learning. 8. Addressing Vertical Partitioning Issues in Federated Learning. 9. Use Cases. | ||
| 650 | _aMachine Learning | ||
| 650 | _aArtificial Intelligence | ||
| 650 | _aApprentissage Automatique | ||
| 650 | _aArtificial Intelligence - Industrial Applications | ||
| 650 | _aMachine Learning - Industrial Applications | ||
| 856 | _3www.perlego.com | ||
| 942 | _cTXT | ||
| 999 |
_c106384 _d106383 |
||