Thorbis AI - Engagement Prediction Model 🤖

Overview

Thorbis AI is a machine learning system that predicts and optimizes website content engagement. Think of it as a smart assistant that learns from how users interact with your website and suggests what content might work better.

How It Works 🔄

Data Collection
- Tracks user interactions (clicks, hover time, etc.)
- Monitors how long users engage with content
- Records which version (A or B) of content performs better
Learning Process
- The AI analyzes patterns in user behavior
- Learns what combinations of features lead to better engagement
- Continuously improves its predictions through training
Predictions
- Predicts engagement scores for content
- Suggests which content variant might perform better
- Provides confidence levels for its predictions

Features ✨

Real-time Predictions: Get instant feedback on content performance
A/B Testing: Automated testing of different content versions
Engagement Scoring: Numerical scores for content performance
Smart Optimization: AI-driven content recommendations

Technical Details 🛠️

Architecture

Built with TensorFlow.js
Uses deep learning with multiple neural network layers
Implements both regression (scoring) and classification (variant selection)

Model Structure

Input Layer: 7 features (clicks, hover time, etc.)
Hidden Layers: 128 → 64 → 32 neurons
Output: Engagement score and variant prediction

Getting Started 🚀

Installation
```
npm install
```
Training the Model
```
npm run train
```
Running Predictions
```
npm run start
```

Usage Examples 📝

// Initialize the model
const model = new EngagementModel();
await model.initialize();

// Make predictions
const prediction = await model.predict({

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byronwade/thorbis-ai