Train models without leaking your test data.
What it does
Guides the training and evaluation of machine learning models with data preparation and safeguards against common training problems.
When to use it
Use for classification, regression, neural networks, hyperparameter tuning, or troubleshooting overfitting, underfitting, and convergence problems.
How to use it
Give it training data; it produces trained models and evaluation results using the illustrated training workflows.
What you provide
- Your files
What you need · 3
The data preparation and training examples run as Python code; no Python version is specified.
The data preparation example imports pandas to load and clean CSV data.
The shared data preparation workflow uses scikit-learn for splitting data, scaling features, and encoding labels.
Access · 0
No additional actions listed.