AI Models
AI-guided insights tailored to your data. Smart suggestions in seconds. Let our AI assistant analyze your metrics and recommend your next move.
What You Get
AI-generated suggestions for the best ML model to use (e.g., TabNet, LightGBM).
Preprocessing steps: handle skewness, missing data, encoding, etc.
Class imbalance remedies: SMOTE, class weights.
Visual explanations of anomalies and feature impact.
Dynamic prompt generation based on your dataset's metrics.
Top AI Models Insights
Smart Model Suggestions: Based on your metrics, the AI recommends models (e.g., TabNet, RandomForest, XGBoost) with pros/cons per use case.
Preprocessing Advice Included: AI also suggests how to prepare data — e.g., normalize skewed features, encode high-cardinality columns, or fill nulls.
Dynamic Prompt-to-Insight: AI prompts include user metrics, problem type (classification/regression), and issues — leading to real-time feedback.
Insight Categories: Users receive advice in 3 clear sections: Preprocessing, Model Fit, and Monitoring/Production Readiness.
Handles Missing Context: If metrics are insufficient, the AI replies with clarifying questions — e.g., 'Please provide the target column type.'
Anomaly-Specific Tips: If Outlier_Score or Anomaly_Count is high, the model suggests using IsolationForest or robust scalers.
Label Quality Detection: AI notices high Label_Noise_Rate and advises rechecking labels or applying noise-robust training.
Explainability-Friendly Output: Recommendations are written in both beginner-friendly and expert modes — using toggles like '🔍 Expert Mode.'