Missing values in your dataset? Here's what to do

n this Neural Designer tutorial, we explain how to handle missing values as part of the data preprocessing workflow before training your neural network.

You'll see:
🔹 How Neural Designer marks excluded instances automatically
🔹 How to apply mean and median imputation directly in the tool
🔹 How to choose the best imputation method based on your data distribution

Handling missing data correctly is one of the first steps toward building a high-quality, reliable machine learning model. This short guide gives you everything you need to make the right decision for your specific dataset.
Try neural designer for free: https://www.neuraldesigner.com/downloads

Neural Designer (no-code ML platform): https://www.neuraldesigner.com
Tutorials & examples: https://www.neuraldesigner.com/learning
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