Graphite Note Insights Lifecycle
No-code, Automated Machine Learning for Data Analytics Teams
Last updated
No-code, Automated Machine Learning for Data Analytics Teams
Last updated
Dataset: Begin with a dataset containing historical data.
Feature Selection: Identify the most important variables (features) for the model.
Best Algorithm Search: Test different algorithms to find the best fit for your data.
Model Generation: Create a predictive model based on selected features and the best algorithm.
Model Tuning: Fine-tune the model’s parameters to improve accuracy.
Model Deployment: Deploy the final model for real-world usage.
Explore Key Drivers: Analyze the key factors influencing the model’s predictions.
Explore What-If Scenarios: Test different hypothetical situations to see their impact.
Predict Future Outcomes: Use the model to forecast future trends or outcomes.
