使用集合让一切井井有条
根据您的偏好保存内容并对其进行分类。
将机器学习功能添加至您的应用
使用 Firebase 机器学习训练和部署自定义模型，或者使用 Cloud Vision API 的交钥匙解决方案。
plat_ios
plat_android
部署在设备上运行的自定义模型
无论您使用现有的 TensorFlow Lite 模型l开始，还是训练您自己的模型，都可以使用 Firebase 机器学习模型部署通过无线方式将模型分发给用户。这样可以减少应用的初始安装大小，因为模型只在需要时才会被设备下载。此外，还允许您对多个模型进行 A/B 测试，评估模型性能并定期更新模型，而无需重新发布整个应用。只需上传模型至 Firebase 控制台，我们就会负责托管该模型并将其用于您的应用。如果您愿意的话，也可以使用 Firebase Admin SDK 直接从机器学习生产流水线或 Colab 笔记本部署模型。
使用交钥匙 API 应对常见的用例
Firebase 机器学习套件包含一组基于云的现成 API，适用于以下常见的移动使用场景：识别文字、为图片加标签和识别地标。与基于设备的 API 不同，这些 API 可以利用 Google Cloud 机器学习技术的强大功能提供更高的准确度。您只需将数据传递到库，库就会无缝地向运行在 Google Cloud 上的模型发出请求，然后返回所需的信息 - 只需几行代码即可实现。
eBay Motors 使用 Firebase ML 快速对图片进行分类、降低成本并改善用户体验
eBay Motors 让用户可以搜索和查找他们所在地区要出售的汽车。详细了解他们如何使用 Firebase 机器学习套件中的 AutoML Vision Edge 创建自己的模型和改善用户体验。
查看详情
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Learn how to get started with ML by reviewing our technical documentation.
[null,null,[],[],[],null,["Firebase Machine Learning\n^BETA^\n\nMachine learning for mobile developers \n[Get started](https://console.firebase.google.com/project/_/ml/apis) [View docs\n*arrow_forward*](/docs/ml) \n\nAdd machine learning capabilities to your app \nUse Firebase ML to train and deploy custom models, or use a more turn-key solution with the Cloud Vision APIs. \n*plat_ios* *plat_android* \n\nDeploy custom models that run on-device \nWhether you are starting with an existing [TensorFlow Lite model](https://www.tensorflow.org/lite/models) or training your own, you can use Firebase ML model deployment to distribute models to your users over the air. This reduces initial app installation size since models are downloaded by the device only when needed. It also allows you to A/B test multiple models, evaluate their performance and update models regularly without having to republish your entire app. Just [upload your model](/docs/ml/manage-hosted-models) to the Firebase console, and we'll take care of hosting and serving it to your app. Or if you prefer, you can deploy models directly from your ML production pipeline or Colab notebook [using the Firebase Admin SDK](/docs/ml/manage-hosted-models#manage_models_with_the_firebase_admin_sdk). \n\nSolve for common use cases with turn-key APIs \nFirebase ML also comes with a set of ready-to-use cloud-based APIs for common mobile use cases: [recognizing text](/docs/ml/recognize-text), [labeling images](/docs/ml/label-images), and [recognizing landmarks](/docs/ml/recognize-landmarks). Unlike on-device APIs, these APIs leverage the power of Google Cloud's machine learning technology to give a high level of accuracy. You simply pass in data to the library, which seamlessly makes a request to models running on Google Cloud, and get back the information you need--all in a few lines of code. \nCase Studies \n\neBay Motors uses Firebase ML to quickly categorize images, reduce costs and improve user experience\n\n\neBay Motors allows users to search and find cars for sale in their area. Learn how they used AutoML Vision Edge in Firebase ML to create their own model and improve the user experience.\n[Read more\n*arrow_forward*](/case-studies/ebay) \n\nDocumentation \nLearn how to get started with ML by reviewing our technical documentation. \n[View docs](/docs/ml) \n\nPricing \nUnderstand ML pricing. \n[View pricing](/pricing#firebase-ml) \nTry Firebase today\n\n\nIntegrating it into your app is easy.\n[Get started](https://console.firebase.google.com/) \n\nAll Firebase products \n\nBuild\n\n- [App Check](/products/app-check)\n- [App Hosting](/products/app-hosting)\n- [Authentication](/products/auth)\n- [Cloud Functions](/products/functions)\n- [Cloud Storage](/products/storage)\n- [Data Connect](/products/data-connect)\n- [Extensions](/products/extensions)\n- [Firestore](/products/firestore)\n- [Firebase ML](/products/ml)\n- [Genkit](https://genkit.dev/)\n- [Hosting](/products/hosting)\n- [Realtime Database](/products/realtime-database)\n- [Firebase AI Logic client SDKs](/products/firebase-ai-logic)\n\n[Generative AI](/products/generative-ai) \n\nRun\n\n- [A/B Testing](/products/ab-testing)\n- [App Distribution](/products/app-distribution)\n- [Cloud Messaging](/products/cloud-messaging)\n- [Crashlytics](/products/crashlytics)\n- [Google Analytics](/products/analytics)\n- [In-App Messaging](/products/in-app-messaging)\n- [Performance Monitoring](/products/performance)\n- [Remote Config](/products/remote-config)\n- [Test Lab](/products/test-lab)"]]
