- 了解软件开发周期
- 具有构建或使用 Machine Learning 模型的经验
- 熟悉 Python 编程
观众
- ML工程师
- DevOps 工程师
- 数据工程师
- 基础设施工程师
- 软件开发人员
MLOps 是一套用于结合 Machine Learning 和 DevOps 实践的工具和方法。MLOps 的目标是自动化和优化生产中 ML 系统的部署和维护。
这种以讲师为主导的现场培训（现场或远程）针对的是希望评估当今可用的方法和工具的工程师，以便就在其组织内采用MLOps的前进道路做出明智的决定。
在培训结束时，参与者将能够：
- 安装和配置各种 MLOps 框架和工具。
- 组建一支具有正确技能的正确团队，以构建和支持 MLOps 系统。
- 准备、验证和版本控制数据以供 ML 模型使用。
- 了解 ML 管道的组件以及构建管道所需的工具。
- 尝试使用不同的机器学习框架和服务器进行部署到生产环境。
- 操作整个 Machine Learning 过程，使其可复制和可维护。
课程形式
- 互动讲座和讨论。
- 大量的练习和练习。
- 在现场实验室环境中实际实施。
课程定制选项
- 如需申请此课程的定制培训，请联系我们进行安排。
介绍
- Machine Learning 模型与传统软件的对比
DevOps 工作流概述
Machine Learning 工作流概述
ML 即代码加数据
ML 系统的组件
案例研究：销售 Forecasting 应用程序
Accessing 数据
验证数据
数据转换
从数据管道到 ML 管道
构建数据模型
训练模型
验证模型
再现模型训练
部署模型
将经过训练的模型提供到生产环境
测试 ML 系统
持续交付编排
监视模型
数据版本控制
调整、扩展和维护 MLOps 平台
故障 排除
总结和结论
United Arab Emirates - MLOps: CI/CD for Machine Learning
Qatar - MLOps: CI/CD for Machine Learning
Egypt - MLOps: CI/CD for Machine Learning
Saudi Arabia - MLOps: CI/CD for Machine Learning
South Africa - MLOps: CI/CD for Machine Learning
Brasil - MLOps: CI/CD for Machine Learning
Canada - MLOps: CI/CD for Machine Learning
中国 - MLOps: CI/CD for Machine Learning
香港 - MLOps: CI/CD for Machine Learning
澳門 - MLOps: CI/CD for Machine Learning
台灣 - MLOps: CI/CD for Machine Learning
USA - MLOps: CI/CD for Machine Learning
Österreich - MLOps: CI/CD for Machine Learning
Schweiz - MLOps: CI/CD for Machine Learning
Deutschland - MLOps: CI/CD for Machine Learning
Czech Republic - MLOps: CI/CD for Machine Learning
Denmark - MLOps: CI/CD for Machine Learning
Estonia - MLOps: CI/CD for Machine Learning
Finland - MLOps: CI/CD for Machine Learning
Greece - MLOps: CI/CD for Machine Learning
Magyarország - MLOps: CI/CD for Machine Learning
Ireland - MLOps: CI/CD for Machine Learning
Luxembourg - MLOps: CI/CD for Machine Learning
Latvia - MLOps: CI/CD for Machine Learning
España - MLOps: CI/CD for Machine Learning
Italia - MLOps: CI/CD for Machine Learning
Lithuania - MLOps: CI/CD for Machine Learning
Nederland - MLOps: CI/CD for Machine Learning
Norway - MLOps: CI/CD for Machine Learning
Portugal - MLOps: CI/CD for Machine Learning
România - MLOps: CI/CD for Machine Learning
Sverige - MLOps: CI/CD for Machine Learning
Türkiye - MLOps: CI/CD for Machine Learning
Malta - MLOps: CI/CD for Machine Learning
Belgique - MLOps: CI/CD for Machine Learning
France - MLOps: CI/CD for Machine Learning
日本 - MLOps: CI/CD for Machine Learning
Australia - MLOps: CI/CD for Machine Learning
Malaysia - MLOps: CI/CD for Machine Learning
New Zealand - MLOps: CI/CD for Machine Learning
Philippines - MLOps: CI/CD for Machine Learning
Singapore - MLOps: CI/CD for Machine Learning
Thailand - MLOps: CI/CD for Machine Learning
Vietnam - MLOps: CI/CD for Machine Learning
Argentina - MLOps: CI/CD for Machine Learning
Chile - MLOps: CI/CD for Machine Learning
Costa Rica - MLOps: CI/CD for Machine Learning
Ecuador - MLOps: CI/CD for Machine Learning
Guatemala - MLOps: CI/CD for Machine Learning
Colombia - MLOps: CI/CD for Machine Learning
México - MLOps: CI/CD for Machine Learning
Panama - MLOps: CI/CD for Machine Learning
Peru - MLOps: CI/CD for Machine Learning
Uruguay - MLOps: CI/CD for Machine Learning
Venezuela - MLOps: CI/CD for Machine Learning
Polska - MLOps: CI/CD for Machine Learning
United Kingdom - MLOps: CI/CD for Machine Learning
South Korea - MLOps: CI/CD for Machine Learning
Bulgaria - MLOps: CI/CD for Machine Learning
Bolivia - MLOps: CI/CD for Machine Learning
Indonesia - MLOps: CI/CD for Machine Learning
Kazakhstan - MLOps: CI/CD for Machine Learning
Moldova - MLOps: CI/CD for Machine Learning
Morocco - MLOps: CI/CD for Machine Learning
Tunisia - MLOps: CI/CD for Machine Learning
Kuwait - MLOps: CI/CD for Machine Learning
Oman - MLOps: CI/CD for Machine Learning
Slovakia - MLOps: CI/CD for Machine Learning
Kenya - MLOps: CI/CD for Machine Learning
Nigeria - MLOps: CI/CD for Machine Learning
Botswana - MLOps: CI/CD for Machine Learning
Slovenia - MLOps: CI/CD for Machine Learning
Croatia - MLOps: CI/CD for Machine Learning
Serbia - MLOps: CI/CD for Machine Learning
Bhutan - MLOps: CI/CD for Machine Learning