Responsible AI in the Enterprise
Practical AI risk management for explainable, auditable, and safe models with hyperscalers and Azure OpenAI
Created by Heather Dawe, Adnan Masood
Explore how to build ethical, transparent, and compliant AI systems for your organization. Learn to manage AI risks, ensure fairness, and use leading cloud tools for explainability and governance. Gain practical skills to create models that are both auditable and safe for enterprise use.
Packt | Jul 2023 | 318 min
What You Will Learn
You will start by understanding the foundations of responsible AI, including risk management and model governance. Through practical examples and hands-on exercises, you will explore fairness toolkits and interpretability methods from major cloud providers. By applying these tools, you will gain confidence in building and managing explainable, auditable AI models.
Key Features
- Apply fairness and bias mitigation techniques using FairLearn and other cloud tools
- Monitor, interpret, and govern machine learning models for transparency and compliance
- Build explainable models with practical methods like feature summaries and counterfactuals
Target Audience
Ideal for data scientists, machine learning engineers, and IT professionals who want to implement ethical AI in their organizations. If you already have experience building machine learning models and are looking to ensure fairness, transparency, and compliance in enterprise settings, you will find actionable guidance and practical tools here.
