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如何在手机上实现机器学习模型？

[英]How to implement machine learning models on mobile phones?

原文 2018-12-13 06:58:12 0 2 android/ python/ ios/ machine-learning

I've built Machine Learning Models Random Forest and XGBOOST on Python or R 我在Python或R上构建了机器学习模型随机森林和XGBOOST

How can I implement that my model work in mobile phone IOS / Android? 如何在手机IOS / Android中实现我的模型？ Not for training, just to predict the probability for users by properties and events. 不用于培训，只是为了通过属性和事件预测用户的概率。

2 个解决方案

You can expose your machine learning model as a REST API endpoint. 您可以将machine learning模型公开为REST API端点。 Essentially, the client (mobile) will be making requests at a specific endpoint, which will then be triggering your model. 本质上，客户端（移动）将在特定端点发出请求，然后触发您的模型。

There quite a few examples available in the Web for you to read but for your convenience you may take a look at this one . 在Web供您阅读，但为了您的方便，你可以看看这个可以有相当多的例子一个。

I think I'm qualified to answer this because it was yesterday that I viewed Google's "DevFestOnAir 2018". 我想我有资格回答这个问题，因为昨天我看过Google的“DevFestOnAir 2018”。 There was an "End to End Machine Learning" talk where the speaker mentioned what TensorFlow(TF) has to support AI in mobile devices. 有一个“端到端机器学习”的演讲，演讲者提到了TensorFlow（TF）在移动设备中支持AI的内容。

Now, TF is available for JS , Java and many other languages, so this captures the entirety of the model that runs on your PC, uses other functionalities to make it run on lesser RAM and Processors. 现在，TF可用于JS，Java和许多其他语言，因此它捕获了在PC上运行的整个模型，使用其他功能使其在较小的RAM和处理器上运行。 Do check this out. 请检查一下。 If I'm not wrong TF has a feature that would do the conversion for you. 如果我没错，TF有一个功能可以为你做转换。