Maximizing Your Model Potential: Custom Dataset vs. Cross-Validation

Author(s): Jan Marcel Kezmann

Originally published on Towards AI.

Achieving Peak Performance: Mastering Control and Generalization

Source: Image created by Jan Marcel Kezmann

Today, we’re going to explore a crucial decision that researchers and practitioners face when training machine and deep learning models: Should we stick to a fixed custom dataset or embrace the power of cross-validation techniques?

Data is the lifeblood of ML and DL models, serving as the foundation upon which they learn and make predictions.

But the question of how to best utilize that data remains a topic of debate. Some swear by the reliability and control offered by a fixed custom dataset, while others advocate for the flexibility and robustness of cross-validation.

In this blog post,… Read the full blog for free on Medium.

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Published via Towards AI