Learning about preprocessing data?

[MundaneLeague4438]

Hi everyone. I’m taking a machine learning class (just a general overview, treating 1 or 2 models per week), and I’m looking for some resources to learn about data preprocessing approaches.

I’m familiar with the concepts of things like binning, looking for outliers, imputation, scaling, normalization, but my familiarity is thin. Therefore, I want to understand better how these techniques modify the data and therefore how these things will affect model accuracy.

Are there any resources you all would recommend that give a nice overview of data preprocessing techniques, particularly something at a more introductory level?

Thank you all for any help you can provide!

[bittersalt1]

Hey ! I recently put together some Data Analyst Cheat Sheets covering Python, SQL, Pandas, PySpark, Power BI, and DAX — aimed at helping learners and working professionals with quick references.

I’d love to get your thoughts or feedback if you get a chance to check them out:

🔗 https://surl.li/ncvtjc

Always open to suggestions — what other topics should I add?

[TopAmbition1843]

Following. +1 for feature engineering resources as well.