other · 2025
Data Pre-processing
Parteek Bhatia
Cited by 0Abstract and details only
Abstract
Machine learning has become a dominant problem-solving technique in the modern world, with applications ranging from search engines and social media to self-driving cars and artificial intelligence. This lucid textbook presents the theoretical foundations of machine learning algorithms, and then illustrates each concept with its detailed implementation in Python to allow beginners to effectively implement the principles in real-world applications. All major techniques, such as regression, classification, clustering, deep learning, and association mining, have been illustrated using step-by-step coding instructions to help inculcate a 'learning by doing' approach. The book has no prerequisites, and covers the subject from the ground up, including a detailed introductory chapter on the Python language. As such, it is going to be a valuable resource not only for students of computer science, but also for anyone looking for a foundation in the subject, as well as professionals looking for a ready reckoner.
Cite this paper
Bhatia, P. (2025). Data Pre-processing. https://doi.org/10.1017/9781009170239.006
Bhatia, Parteek. “Data Pre-processing.” 2025, pp. 125–54, https://doi.org/10.1017/9781009170239.006.
Bhatia, Parteek. 2025. “Data Pre-processing.” https://doi.org/10.1017/9781009170239.006.
Bhatia, P. (2025) ‘Data Pre-processing’. Available at: https://doi.org/10.1017/9781009170239.006.
@misc{bhatia2025data,
title = {{Data Pre-processing}},
author = {Bhatia, Parteek},
pages = {125--154},
year = {2025},
doi = {10.1017/9781009170239.006}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
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