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AI Workflow: Feature Engineering and Bias Detection

AI Workflow: Feature Engineering and Bias Detection

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9.0/10 (Our Score)
Product is rated as #18 in category Artificial Intelligence

This is the third course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 3 introduces you to the next stage of the workflow for our hypothetical media company. In this stage of work you will learn best practices for feature engineering, handling class imbalances and detecting bias in the data. Class imbalances can seriously affect the validity of your machine learning models, and the mitigation of bias in data is essential to reducing the risk associated with biased models. These topics will be followed by sections on best practices for dimension reduction, outlier detection, and unsupervised learning techniques for finding patterns in your data. The case studies will focus on topic modeling and data visualization. By the end of this course you will be able to: 1. Employ the tools that help address class and class imbalance issues 2. Explain the ethical considerations regarding bias in data 3. Employ ai Fairness 360 open source libraries to detect bias in models 4. Employ dimension reduction techniques for both EDA and transformations stages …

Instructor Details

Mark J. Grover is a member of the IBM Data & AI Learning team and specializes in creating and delivering online content. He comes to IBM from Cape Fear Community College in Wilmington, NC where he was a full time professor of computer technology. He was one of the coordinators for their Information Security program and taught courses in Computer Security, Network Administration, System Administration, and Microsoft Office. He was the lead Cisco instructor and faculty advisor to the school’s annual Cisco Netriders networking competition. During his tenure, he was recognized as a Cisco Instructor of Excellence – Expert level and was nominated for US Professor of the Year. Prior to teaching, Mark owned and operated a computer sales and service company for over 13 years. He then transitioned to a position working at the University of North Carolina Wilmington providing enterprise computer support, where he achieved the highest award for a staff member: The Award for Excellence in Innovation. Mark brings over 25 years of information technology experience to IBM. His passion includes camping, hiking, mountain biking, and spending time with his family. He is happily married and has two kids.

Specification: AI Workflow: Feature Engineering and Bias Detection

Duration 4 hours
Year 2020
Level Expert
Certificate Yes
Quizzes Yes

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AI Workflow: Feature Engineering and Bias Detection
AI Workflow: Feature Engineering and Bias Detection

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