Try these codelabs to learn hands-on how Firebase can help you use TensorFlow Lite models more easily and effectively.
Digit classification (introduction to model deployment)
Learn how to use Firebase's model deployment features by building an app that recognizes handwritten digits. Deploy TensorFlow Lite models with Firebase ML, analyze model performance with Performance Monitoring, and test model effectiveness with A/B Testing.
Sentiment analysis
In this codelab, you use your own training data to fine-tune an existing text classification model that identifies the sentiment expressed in a passage of text. Then, you deploy the model using Firebase ML and compare the accuracy of the old and new models with A/B Testing.
Content recommendation
Recommendation engines let you personalize experiences to individual users, presenting them with more relevant and engaging content. Rather than building out a complex pipeline to power this feature, this codelab shows how you can implement a content recommendation engine for an app by training and deploying an on-device ML model.