Data Cleaning and Exploration with Machine Learning
Get to grips with machine learning techniques to achieve sparkling-clean data quickly
Michael Walker
BIRMINGHAM—MUMBAI
Data Cleaning and Exploration with Machine Learning
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ISBN 978-1-80324-167-8
Contributors
About the author
Michael Walker has worked as a data analyst for over 30 years at a variety of educational institutions. He has also taught data science, research methods, statistics, and computer programming to undergraduates since 2006. He is currently the Chief Information Officer at College Unbound in Providence, Rhode Island.
About the reviewers
Kalyana Bedhu is an engineering leader for data science at Microsoft. Kalyana has over 20 years of industry experience in data analytics across various companies such as Ericsson, Sony, Bosch Fidelity, and Oracle, among others. Kalyana was an early practitioner of data science at Ericsson, setting up a data science lab and building up competence in solving some practical data science problems. He played a pivotal role in transforming a central IT organization that dealt with most of the enterprise business intelligence, data, and analytical systems, into an AI and data science engine. Kalyana is a recipient of patents, a speaker, and has authored award-winning papers and data science courses.
Divya Sardana serves as the lead AI/ ML engineer at Nike. Previously, she was a senior data scientist at Teradata Corp. She holds a Ph.D. in computer science from the University of Cincinnati, OH. She has experience working on end-to-end machine learning and deep learning problems involving techniques such as regression and classification. She has further experience in moving developed models to production and ensuring scalability. Her interests include solving complex big data and machine learning/deep learning problems in real-world domains. She is actively involved in the peer review of journals and books in the area of machine learning. She has served as a session chair at machine learning conferences such as ICMLA 2021 and BDA 2021.