TensorFlow For Dummies

Index

A

1. abs function, 36
2. accumulation, momentum algorithm, 75–76
3. activation functions
   1. classifier functions, 126–127
   2. overview, 121, 123–124
   3. rectifier functions, 124–126
   4. saturation, 136–137
   5. training with backpropagation, 129
4. activation parameter, 157, 185
5. activation_fn parameter, 138, 144, 145, 147
6. activity_regularizer parameter, 157
7. AdagradOptimizer class, 76–77
8. AdamOptimizer class, 77–78
9. adaptive gradient algorithm, 76–77
10. add function, 36
11. add_event method, 60, 61–62
12. add_graph method, 60, 62
13. add_loss method, 185
14. add_meta_graph method, 61, 62, 85
15. add_meta_graph_and_variables function, 85, 86
16. add_n function, 36
17. add_run_metadata method, 61
18. add_session_log method, 61
19. add_summary method, 60, 61, 64, 89–90
20. add_to_collection method, 47
21. add_to_collections method, 47
22. add_update method, 185
23. add_variable method, 185
24. adjust_brightness function, 169, 170
25. adjust_contrast function, 169, 170, 175
26. adjust_gamma function, 169, 170
27. adjust_hue function, 169, 170
28. adjust_saturation function, 169, 170
29. Advanced Package Tool (APT), 20
30. after_create_session method, 91
31. after_run method, 91, 92
32. allocator_type field, 238
33. allow_growth field, 237, 238
34. allow_soft_placement option, 227
35. AlphaGo program, Google, 1, 129
36. app group, gcloud, 282
37. apply_regularization function, 141
38. arg_scope function, 143, 147
39. argmax function, 37, 38
40. argmin function, 37, 38
41. args field, 301
42. argument scope, 143
43. arrays. See tensors
44. artificial neural networks (ANNs). See neural networks
45. as_cluster_def method, 270
46. as_default method, 46