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课程大纲
介绍
- ML Kit 与 TensorFlow 与其他机器学习服务
- ML Kit 功能和组件概述
开始
- 设置 ML Kit SDK
- 探索 API 和示例应用
实现 ML Kit 视觉 API
- 自动输入数据(文本识别)
- 检测自拍和人像的人脸(人脸检测)
- 解释身体姿势(姿势检测)
- 添加背景效果(自拍分割)
- 集成条码扫描
- 识别物体、地点、物种等(图像标注)
- 定位图像中的突出对象(对象检测和跟踪)
- 识别手写文本(数字墨迹识别)
使用自然语言 API
- 识别语言
- 翻译文本
- 生成智能回复
- 使用实体提取
使用 ML Kit 优化现有应用程序
- 将自定义模型与 ML Kit 一起使用
- 从 Firebase 迁移到新的 ML Kit SDK
- 从 Mobile Vision 迁移到 ML Kit SDK
- 减小部署的应用大小
- 重构应用以使用动态功能模块
疑难解答提示
摘要和后续步骤
要求
- 对机器学习的理解
- 具有移动开发经验
观众
- 软件工程师
- 移动应用开发者
14 小时
客户评论 (3)
The details and the presentation style.
Cristian Mititean - Accenture Industrial SS
课程 - Azure Machine Learning (AML)
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
课程 - Artificial Neural Networks, Machine Learning, Deep Thinking
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete