计算机视觉机器学习实践(影印版)
Valliappa Lakshmanan, Martin Gorner, Ryan Gillard
出版时间:2022年06月
页数:463
“本书全面介绍了深度计算机视觉的最新技术,以及在 Keras中构建端到端生产系统以解决实际问题的最佳实践。”
一Francois Chollet深度学习研究员以及Keras创造者

本书向你展示了如何使用机器学习(ML)模型从图像中提取信息。ML工程师和数据科学家将学习行之有效的ML技术来解决各种图像问题,包括分类、目标检测、自动编码器、图像生成、计数和添加字幕。本书很好地介绍了端到端的深度学习:数据集创建、数据预处理、模型设计、模型训练、评估、部署和可解释性。
Google工程师Valliappa Lakshmanan、Martin Gorner、Ryan Gillard为你展示了如何开发精准且可解释的计算机视觉ML模型,并以灵活且可维护的方式使用健壮的ML架构将其投入大规模生产。你将学习如何使用TensorFlow和Keras编写的模型进行设计、训练、评估和预测。
你会学到:
● 为计算机视觉任务设计ML架构
● 选择适合任务的模型(比如ResNet、SqueezeNet或EfficientNet)
● 创建端到端的ML管道来训练、评估、部署、解释你的模型
● 对图像进行预处理,以增强数据并支持可学习性
● 结合可解释性和可靠的AI最佳实践
● 将图像模型部署为Web服务或边缘设备
● 监测和管理ML模型
● 使用协作过滤设计出一套仿Netflix的推荐系统
  1. Preface
  2. 1. Machine Learning for Computer Vision
  3. Machine Learning
  4. Deep Learning Use Cases
  5. Summary
  6. 2. ML Models for Vision
  7. A Dataset for Machine Perception
  8. A Linear Model Using Keras
  9. A Neural Network Using Keras
  10. Summary
  11. Glossary
  12. 3. Image Vision
  13. Pretrained Embeddings
  14. Convolutional Networks
  15. The Quest for Depth
  16. Modular Architectures
  17. Neural Architecture Search Designs
  18. Beyond Convolution: The Transformer Architecture
  19. Choosing a Model
  20. Summary
  21. 4. Object Detection and Image Segmentation
  22. Object Detection
  23. Segmentation
  24. Summary
  25. 5. Creating Vision Datasets
  26. Collecting Images
  27. Data Types
  28. Manual Labeling
  29. Labeling at Scale
  30. Automated Labeling
  31. Bias
  32. Creating a Dataset
  33. Summary
  34. 6. Preprocessing
  35. Reasons for Preprocessing
  36. Size and Resolution
  37. Training-Serving Skew
  38. Data Augmentation
  39. Forming Input Images
  40. Summary
  41. 7. Training Pipeline
  42. Efficient Ingestion
  43. Saving Model State
  44. Distribution Strategy
  45. Serverless ML
  46. Summary
  47. 8. Model Quality and Continuous Evaluation
  48. Monitoring
  49. Model Quality Metrics
  50. Quality Evaluation
  51. Summary
  52. 9. Model Predictions
  53. Making Predictions
  54. Online Prediction
  55. Batch and Stream Prediction
  56. Edge ML
  57. Summary
  58. 10. Trends in Production ML
  59. Machine Learning Pipelines
  60. Explainability
  61. No-Code Computer Vision
  62. Summary
  63. 11. Advanced Vision Problems
  64. Object Measurement
  65. Counting
  66. Pose Estimation
  67. Image Search
  68. Summary
  69. 12. Image and Text Generation
  70. Image Understanding
  71. Image Generation
  72. Image Captioning
  73. Summary
  74. Afterword
  75. Index
书名:计算机视觉机器学习实践(影印版)
国内出版社:东南大学出版社
出版时间:2022年06月
页数:463
书号:978-7-5641-9976-0
原版书书名:Practical Machine Learning for Computer Vision
原版书出版商:O'Reilly Media
Valliappa Lakshmanan
 
Valliappa (Lak) Lakshmanan是Google Cloud的数据分析和AI解决方案负责人。他的团队借助BigQuery和Google Cloud上的其他数据分析、机器学习产品,构建软件解决方案来解决业务问题。

Valliappa Lakshmanan目前是Google云计算平台数据和机器学习专业服务的技术主管。他希望将机器学习普及化,让任何人、在任何地方,无需深入了解统计学、编程知识,也无需购买大量硬件,也可使用Google云平台提供的卓越架构。在加入Google前,Valliappa曾供职于气象局,领导着一个数据科学团队,并且是NOAA国家重大风暴实验室的研究科学家,他曾致力于使用机器学习进行恶劣天气的识别和预测。
 
 
Martin Gorner
 
Martin Gorner是Keras/TensorFlow的产品经理,专注于使用最先进的模型改善开发人员的体验。
 
 
Ryan Gillard
 
Ryan Gillard是Google Cloud专业服务组织的AI工程师,负责为各行各业构建ML模型。他的职业生涯是从医院和保健行业的研究科学家开始的。
 
 
The bird on the cover of Practical Machine Learning for Computer Vision is an emerald toucanet (Aulacorhynchus prasinus), the smallest species of toucan. Central and South America have large populations from the cloud forests of Costa Rica to Venezuela.
Vibrant green feathers camouflage emerald toucanets in the tropics. Adults typically measure 12–13 inches long, weigh just over 5 ounces, and live 10–11 years in the wild. Their beaks are colorful: yellow on top, a white outline, and red or black on the bottom. They eat fruit and insects, as well as small lizards and the eggs and young of other birds. Groups of about eight will hunt and forage together. Emerald toucanets build their nests by enlarging the nests of smaller birds. The male and female trade off shifts in the nest, incubating, feeding, and cleaning their chicks.
Deforestation has driven emerald toucanets into shade coffee farms. Overall, their population is decreasing. Many of the animals on O’Reilly’s covers are endangered; all of them are important to the world.
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定价:148.00元
书号:978-7-5641-9976-0
出版社:东南大学出版社