---
title: "#traintestsplit articles | Hashnode"
description: "Explore 3 articles tagged #traintestsplit on Hashnode. Tutorials, guides, and how-tos from the community."
url: "https://hashnode.com/tag/traintestsplit"
---

Tag

# #traintestsplit

3 posts · 1 followers

[Divyajot Kaur](https://hashnode.com/@djk2004) · [May 27](https://hashnode.com/posts/train-validation-test-data-machine-learning/6a171e5bbadcd8afcb0bf0ac)

### [Part 7: Why We Split Data in Machine Learning?](https://ai-beginners-journey.hashnode.dev/train-validation-test-data-machine-learning?utm_source=hashnode&utm_medium=feed)

Understanding training, validation, and test datasets in a simple way

5 min read · [ai-beginners-journey.hashnode.dev](https://ai-beginners-journey.hashnode.dev/train-validation-test-data-machine-learning?utm_source=hashnode&utm_medium=feed)

[Sukrit Deb](https://hashnode.com/@sukrit00) · [Sep 17, 2025](https://hashnode.com/posts/why-we-use-fittransform-for-training-data-but-only-transform-for-testing-data/68caefe7904cde8f3e033c20)

### [Why we use fit\_transform() for Training Data but only transform() for Testing Data](https://sukrit00.hashnode.dev/why-we-use-fittransform-for-training-data-but-only-transform-for-testing-data?utm_source=hashnode&utm_medium=feed)

When you start working with machine learning pipelines, one of the first things you’ll notice is that we often write code like this: from sklearn.preprocessing import StandardScaler scaler = StandardScaler() # Training set X\_train\_scaled = scaler...

3 min read · [sukrit00.hashnode.dev](https://sukrit00.hashnode.dev/why-we-use-fittransform-for-training-data-but-only-transform-for-testing-data?utm_source=hashnode&utm_medium=feed)

[Rhythm Rawat](https://hashnode.com/@Rhythm1821) · [Apr 22, 2023](https://hashnode.com/posts/train-test-split-importance-use-cases-and-practical-implementation/6443df5261f861a859a5dc1e)

### [Train Test Split: Importance, Use Cases, and Practical Implementation](https://rhythmblogs.hashnode.dev/train-test-split-importance-use-cases-and-practical-implementation?utm_source=hashnode&utm_medium=feed)

Machine learning models are trained on data to make predictions or classifications on new data. However, if the same data is used for training and testing the model, the model will memorize the data and perform poorly on new data. To avoid this probl...

3 min read · [rhythmblogs.hashnode.dev](https://rhythmblogs.hashnode.dev/train-test-split-importance-use-cases-and-practical-implementation?utm_source=hashnode&utm_medium=feed)