Course Outline
Introduction to Deep Learning Explainability for Government
- What are black-box models?
- The importance of transparency in AI systems for government
- Overview of explainability challenges in neural networks for government operations
Advanced XAI Techniques for Deep Learning for Government
- Model-agnostic methods for deep learning: LIME, SHAP
- Layer-wise relevance propagation (LRP)
- Saliency maps and gradient-based methods
Explaining Neural Network Decisions for Government
- Visualizing hidden layers in neural networks for government use cases
- Understanding attention mechanisms in deep learning models for government applications
- Generating human-readable explanations from neural networks for government stakeholders
Tools for Explaining Deep Learning Models for Government
- Introduction to open-source XAI libraries for government use
- Using Captum and InterpretML for deep learning in government agencies
- Integrating explainability techniques in TensorFlow and PyTorch for government projects
Interpretability vs. Performance for Government
- Trade-offs between accuracy and interpretability for government decision-making
- Designing interpretable yet performant deep learning models for government applications
- Handling bias and fairness in deep learning for government initiatives
Real-World Applications of Deep Learning Explainability for Government
- Explainability in healthcare AI models for government programs
- Regulatory requirements for transparency in AI for government agencies
- Deploying interpretable deep learning models in production for government operations
Ethical Considerations in Explainable Deep Learning for Government
- Ethical implications of AI transparency for government policies
- Balancing ethical AI practices with innovation for government services
- Privacy concerns in deep learning explainability for government data
Summary and Next Steps for Government
Requirements
- Advanced understanding of deep learning techniques
- Familiarity with Python and deep learning frameworks for government applications
- Experience working with neural networks in complex environments
Audience
- Deep learning engineers for government projects
- AI specialists focused on public sector solutions
Testimonials (5)
Hunter is fabulous, very engaging, extremely knowledgeable and personable. Very well done.
Rick Johnson - Laramie County Community College
Course - Artificial Intelligence (AI) Overview
Very flexible.
Frank Ueltzhoffer
Course - Artificial Neural Networks, Machine Learning and Deep Thinking
I liked the new insights in deep machine learning.
Josip Arneric
Course - Neural Network in R
Ann created a great environment to ask questions and learn. We had a lot of fun and also learned a lot at the same time.
Gudrun Bickelq
Course - Introduction to the use of neural networks
It was very interactive and more relaxed and informal than expected. We covered lots of topics in the time and the trainer was always receptive to talking more in detail or more generally about the topics and how they were related. I feel the training has given me the tools to continue learning as opposed to it being a one off session where learning stops once you've finished which is very important given the scale and complexity of the topic.
