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Ji qi xue xi liu shui xian shi zhan = Building machine learning pipelines /
机器学习流水线实战 = Building machine learning pipelines /
Detailed summary in vernacular field.
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Chino Inglés |
| Publicado: |
Beijing Shi :
Ren min you dian chu ban she,
2021.
|
| Edición: | Di 1 ban. |
| Colección: | Tu ling cheng xu she ji cong shu.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 037 | |a 9787115573216 |b O'Reilly Media | ||
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| 049 | |a UAMI | ||
| 100 | 1 | |a Hapke, Hannes Max, |e author. | |
| 240 | 1 | 0 | |a Building machine learning pipelines. |l Chinese |
| 245 | 1 | 0 | |6 880-01 |a Ji qi xue xi liu shui xian shi zhan = |b Building machine learning pipelines / |c Hanneisi Hapuke, Kaiselin Na'erxun zhu ; Kong Xiaoquan, Zheng Wei, Jiang Jun yi. |
| 246 | 3 | 1 | |a Building machine learning pipelines |
| 250 | |6 880-02 |a Di 1 ban. | ||
| 264 | 1 | |6 880-03 |a Beijing Shi : |b Ren min you dian chu ban she, |c 2021. | |
| 300 | |a 1 online resource : |b illustrations. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |6 880-04 |a Tu ling cheng xu she ji cong shu | |
| 504 | |a Includes bibliographical references. | ||
| 520 | |6 880-05 |a Detailed summary in vernacular field. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 630 | 0 | 0 | |a TensorFlow. |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Cloud computing. | |
| 650 | 0 | |a Business enterprises |x Data processing. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Infonuagique. | |
| 650 | 6 | |a Entreprises |x Informatique. | |
| 650 | 7 | |a Business enterprises |x Data processing. |2 fast |0 (OCoLC)fst00842543 | |
| 650 | 7 | |a Cloud computing. |2 fast |0 (OCoLC)fst01745899 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 700 | 1 | |a Nelson, Catherine, |e author. | |
| 700 | 1 | |6 880-06 |a Kong, Xiaoquan, |e translator. | |
| 830 | 0 | |6 880-07 |a Tu ling cheng xu she ji cong shu. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9787115573216/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 880 | 1 | 0 | |6 245-01/$1 |a 机器学习流水线实战 = |b Building machine learning pipelines / |c 汉内斯·哈普克, 凯瑟琳·纳尔逊 著 ; 孔晓泉, 郑炜, 江骏 译. |
| 880 | |6 250-02/$1 |a 第1版. | ||
| 880 | 1 | |6 264-03/$1 |a 北京市 : |b 人民邮电出版社, |c 2021. | |
| 880 | 1 | |6 490-04/$1 |a 图灵程序设计丛书 | |
| 880 | |6 520-05/$1 |a 正如自动化流水线给汽车制造业带来了质的改变，自动化机器学习流水线也能从根本上加速机器学习领域的发展。机器学习流水线实现了复用、管理和部署机器学习模型的标准化流程。数据科学家和机器学习工程师不仅能摆脫逐个手动构建和训练模型的"作坊式"工作流程，还能产出更可靠、更安全的模型。 本书带领你使用TensorFlow生态圈中的众多工具构建可复现的机器学习流水线，从而将模型部署时间从数天缩短为数分钟，有效地实现机器学习项目产品化。你将学习如下内容。 了解机器学习流水线的构建步骤 使用TensorFlow Extended（TFX）构建机器学习流水线 使用Beam、Airflow、Kubeflow Pipelines编排流水线 数据校验和数据预处理 使用TensorFlow的模型分析工具 检查模型的公平性 使用TensorFlow Serving和TensorFlow Lite部署模型 了解差分隐私、联邦学习和加密机器学习等隐私保护方法. | ||
| 880 | 1 | |6 700-06/$1 |a 孔晓泉, |e translator. | |
| 880 | 0 | |6 830-07/$1 |a 图灵程序设计丛书. | |
| 994 | |a 92 |b IZTAP | ||