From Raw to Refined: Data Preprocessing with Scikit-learn
Year: 2023
Type: article
Abstract: Data preprocessing is often the determining factor in the success of machine learning models, as it involves cleaning, transforming, and enhancing raw data to make it suitable for analysis. Scikit-learn, a powerful Python library, offers an extensive set of tools and techniques for this purpose. This comprehensive guide delves into the practical application of Scikit-learn's pre-processing functionalities, covering data scaling, encoding categorical variables, handling missing values, and feature selection. Through hands-on examples and best practices, readers will gain a deep understanding of how to harness Scikit-learn's capabilities to prepare data effectively for machine learning tasks. Whether you are a novice or an experienced data scientist, this document equips you with the skills needed to unlock the potential of your datasets and improve model performance.
Authors: T. Aditya Sai Srinivas, Md. Kaif Khan, K. Karthik Reddy, G. Sai Chand
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6892646964