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3. Data Analytics: Data Cleaning Challenges Refer to page 18 for problems on data preprocessing. Instructions: . Identify and classify types of data errors (e.g., missing values, duplicates, outliers) in a dataset. • Propose techniques to address each error type and justify the choice of method. • Discuss the impact of poor data quality on machine learning models. Link: [https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qoHazb9tC440AZF/view?usp=sharing]

3. Data Analytics: Data Cleaning Challenges Refer to page 18 for problems on data preprocessing. Instructions: . Identify and classify types of data errors (e.g., missing values, duplicates, outliers) in a dataset. • Propose techniques to address each error type and justify the choice of method. • Discuss the impact of poor data quality on machine learning models. Link: [https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qoHazb9tC440AZF/view?usp=sharing]

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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3. Data Analytics: Data Cleaning Challenges Refer to page 18 for problems on data preprocessing. Instructions: . Identify and classify types of data errors (e.g., missing values, duplicates, outliers) in a dataset. • Propose techniques to address each error type and justify the choice of method. • Discuss the impact of poor data quality on machine learning models. Link: [https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qoHazb9tC440AZF/view?usp=sharing]
Transcribed Image Text:3. Data Analytics: Data Cleaning Challenges Refer to page 18 for problems on data preprocessing. Instructions: . Identify and classify types of data errors (e.g., missing values, duplicates, outliers) in a dataset. • Propose techniques to address each error type and justify the choice of method. • Discuss the impact of poor data quality on machine learning models. Link: [https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qoHazb9tC440AZF/view?usp=sharing]
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