在2016年谷歌创始人的信中，首席执行官Sundar Pichai引用了Google在机器学习和AI的长期投资。“It’s what allows you to use your voice to search for information,” he explained, “to translate the web from one language to another, to filter the spam from your inbox, to search for ‘hugs’ in your photos and actually pull up pictures of people hugging ... to solve many of the problems we encounter in daily life. It’s what has allowed us to build products that get better over time, making them increasingly useful and helpful.”
除了使用自己的产品的机器学习外，谷歌还发布了几种应用机器学习服务 - 愿景，语音，自然语言和翻译 - 并开辟了其Tensorflow可扩展机学习包。基于Tensorflow，云机学习平台的额外服务仍处于封闭的alpha测试阶段。我希望今年晚些时候审查云机学习平台和Tensorflow。
在此预览中，我将仔细查看谷歌云视觉，云语音，云自然语言和云翻译API，并将它们与竞争性净化服务进行比较HPE.那IBM.，和微软。而亚马逊和databricks.同时在云机学习预测中竞争，他们不提供佩带的API。
所有四种Google Machine学习API由Google云平台控制台管理，所有这些都具有RESTful接口;有些人还有RPC接口。有三种身份验证选项;哪一个使用取决于API和用例。
Although it’s easy enough to construct REST client calls in any language that supports HTTP requests and responses, Google may supply client libraries for C#, Dart, Go, Java, JavaScript (browser), Node.js, Objective-C, PHP, Python, and Ruby, depending on the API. I did most of my experimentation in Python, and I used the supplied HTML forms for constructing and testing REST calls.