Build UIs that learn - Discover the powerful combination of UI and AI
Is lazy loading enough? What if your app could predict a user's next click and load the code before they even ask?
#1about 2 minutes
Solving slow load times in single-page apps
React's lazy loading API helps with initial load times but introduces delays when components are actually rendered.
#2about 3 minutes
Prefetching components by predicting user actions
Improve user experience by using dynamic imports to prefetch components or entire routes before the user requests them.
#3about 2 minutes
Applying machine learning to user sequence prediction
Frame user navigation as a sequence prediction problem where the model learns from click history to predict the next action.
#4about 4 minutes
Implementing a neural network with TensorFlow.js
Build a neural network in the browser using TensorFlow.js with LSTM layers and one-hot encoding to handle sequential user interaction data.
#5about 1 minute
Training the prediction model asynchronously in the browser
Use the asynchronous `.fit()` command in TensorFlow.js to train the model with user data in the background without blocking the UI.
#6about 7 minutes
Architecting the solution with the React Context API
Use a `PredictorContext` for ML logic and a `PrefetchContext` as a message bus to decouple prediction triggers from prefetching actions across the application.
#7about 3 minutes
Summary of key techniques for a self-learning UI
A recap of combining React's code splitting, TensorFlow.js for prediction, and Context API for a robust, performance-oriented architecture.
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