Explore practical AI use cases with working prototypes

Develop prototypes informed by demonstrated work in healthcare, forecasting, classification, computer vision, and generative AI.

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What matters

Evaluating whether an AI concept can be implemented
Selecting an appropriate modeling approach for a use case
Creating an interface that demonstrates model behavior

Benefits

Practical prototyping across multiple applied AI domains
Model development combined with software implementation
Experience with traditional machine learning, neural networks, and generative AI

Evidence

Built an AI medical assistant for assisted differential diagnosis based on the Uganda Clinical Guidelines
Developed forecasting, academic success, used-car pricing, insurance, and mushroom classification projects
Created a Stable Diffusion walkthrough from theoretical foundations to implementation

Questions

Which applied AI areas has Silver worked in?

Demonstrated projects cover healthcare AI, forecasting, classification, regression, computer vision, and generative AI.

Interested?

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