ML codelabs
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Try these codelabs to learn hands-on how Firebase can help you use TensorFlow
Lite models more easily and effectively.
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.
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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2026-04-23 UTC."],[],[]]
