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Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool

Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use the What-if Tool to identify potential biases in a model trained on mortgage loan applications.

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What's inside

Syllabus

Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches how to identify biases in AI models, which is key for fairness and accountability in AI systems
Hands-on lab provides practical experience with real-world data, enhancing understanding and application of concepts
Conducted by Google Cloud Training, known for expertise and industry-leading practices in AI

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Activities

Coming soon We're preparing activities for Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. This course can help Data Analysts build a foundation in using AI and machine learning to analyze data. This course can also help Data Analysts identify and mitigate bias in their data analysis.
Statistician
Statisticians analyze data to find trends and patterns. They use their findings to help businesses make informed decisions. This course can help Statisticians build a foundation in using AI and machine learning to analyze data. This course can also help Statisticians identify and mitigate bias in their data analysis.
Machine Learning Engineer
Machine Learning Engineers design and build machine learning models. This course can help Machine Learning Engineers build a foundation in using AI and machine learning to analyze data. This course can also help Machine Learning Engineers identify and mitigate bias in their machine learning models.
Data Scientist
Data Scientists use data to solve complex problems. This course can help Data Scientists build a foundation in using AI and machine learning to analyze data. This course can also help Data Scientists identify and mitigate bias in their data analysis.
Risk Analyst
Risk Analysts identify and assess risks to businesses. This course can help Risk Analysts build a foundation in using AI and machine learning to identify and assess risks. This course can also help Risk Analysts identify and mitigate bias in their risk analysis.
Product Manager
Product Managers develop and manage products. This course can help Product Managers build a foundation in using AI and machine learning to develop products. This course can also help Product Managers identify and mitigate bias in their products.
Actuary
Actuaries use mathematics and statistics to assess risk and uncertainty. This course can help Actuaries build a foundation in using AI and machine learning to assess risk and uncertainty. This course can also help Actuaries identify and mitigate bias in their risk assessment.
Real Estate Agent
Real Estate Agents help people buy and sell homes. This course can help Real Estate Agents build a foundation in using AI and machine learning to assess risk. This course can also help Real Estate Agents identify and mitigate bias in their risk assessment.
Compliance Analyst
Compliance Analysts ensure that businesses comply with laws and regulations. This course can help Compliance Analysts build a foundation in using AI and machine learning to ensure compliance. This course can also help Compliance Analysts identify and mitigate bias in their compliance analysis.
Loan Officer
Loan Officers help people get loans. This course can help Loan Officers build a foundation in using AI and machine learning to assess risk. This course can also help Loan Officers identify and mitigate bias in their risk assessment.
Mortgage Broker
Mortgage Brokers help people get mortgages. This course can help Mortgage Brokers build a foundation in using AI and machine learning to assess risk. This course can also help Mortgage Brokers identify and mitigate bias in their risk assessment.
Underwriter
Underwriters assess risk and determine whether to approve insurance policies. This course can help Underwriters build a foundation in using AI and machine learning to assess risk. This course can also help Underwriters identify and mitigate bias in their risk assessment.
Business Analyst
Business Analysts analyze business processes to identify opportunities for improvement. This course can help Business Analysts build a foundation in using AI and machine learning to analyze business processes. This course can also help Business Analysts identify and mitigate bias in their business analysis.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help Software Engineers build a foundation in using AI and machine learning to develop software systems. This course can also help Software Engineers identify and mitigate bias in their software systems.
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. This course can help Financial Analysts build a foundation in using AI and machine learning to analyze financial data. This course can also help Financial Analysts identify and mitigate bias in their financial analysis.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool.
Sutton and Barto's book classic and foundational text on reinforcement learning, providing a comprehensive overview of the field.
Hastie et. al provides a comprehensive treatment of statistical learning methods with a focus on sparsity, which is particularly important in high-dimensional data analysis.
A practical and accessible guide to deep learning, Howard and Gugger's book focuses on practical implementation with PyTorch and the fastai library.
Molnar's book bridges the gap between conceptual understanding and practical implementation by providing a comprehensive and practical treatment of interpretable machine learning models and techniques.
Brynjolfsson and McAfee take a comprehensive view of the impact of AI on society, economy, and employment, offering insights into the potential challenges and opportunities posed by AI.
Boyd and Vandenberghe's book provides a comprehensive introduction to convex optimization, which is fundamental to many machine learning algorithms.

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