As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.
WHAT YOU WILL LEARN:
- Define predictive models and analyze how companies use them
- Identify how learning algorithms are used in everyday life
- Examine the ability of algorithms to influence and decide human behavior in biased ways, and methods to avoid predictive bias
- Identify vulnerabilities in public data sets and analyze algorithmic privacy violations
In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects [...]