What are some effective debugging techniques for machine learning models?

What are some effective debugging techniques for machine learning models?

Some effective debugging techniques include checking data quality, visualizing model predictions, and using simpler models for comparison.

How can I check the quality of my training data?

You can check for missing values, outliers, and ensure that the data is representative of the problem you're solving.

What visualization tools do you recommend for analyzing model predictions?

Tools like Matplotlib, Seaborn, and TensorBoard are great for visualizing predictions and understanding model performance.

Can you explain how to use simpler models for debugging?

Using simpler models helps you understand the problem better. If a simple model performs well, your complex model might be overfitting.