@ericyocam6Shipped: The Applied AI Universe — Trained AI Model Colle
An open-source collection of trained artificial intelligence and machine learning models supporting Book 1 of The Applied AI Universe Coding Guide.
The repository provides baseline model artifacts across classical machine learning, deep learning, and quantum machine learning, including scikit-learn classifiers, standalone Keras neural networks, quantum circuit parameter files, and symbolic model state.
These artifacts establish the baseline models used throughout the three-book series: Book 1 builds the models, Book 2 explores adversarial attacks against them, and Book 3 evaluates defensive techniques.
Researchers, educators, and AI developers can use the collection to study model architectures, reproduce selected experiments, and investigate how security testing and defensive strategies affect model behavior.
The collection also includes generated figures supporting the educational material. These models are research and learning artifacts rather than production-certified AI systems.
Comments2
Can someone download these models without knowing the books exist, or does the collection point them straight to buying Book 1?
Great question! The models are publicly available on Hugging Face and can be downloaded independently of the books. No purchase is required.
The collection does include links to the three-book series for readers who want additional explanations, code walkthroughs, and context behind the experiments.
My goal is to make the models accessible to researchers, educators, and developers while offering the books as a more structured learning resource. Ideally, someone can start experimenting with the models and then explore the books if they want to go deeper!
2 comments
Can someone download these models without knowing the books exist, or does the collection point them straight to buying Book 1?
Great question! The models are publicly available on Hugging Face and can be downloaded independently of the books. No purchase is required.
The collection does include links to the three-book series for readers who want additional explanations, code walkthroughs, and context behind the experiments.
My goal is to make the models accessible to researchers, educators, and developers while offering the books as a more structured learning resource. Ideally, someone can start experimenting with the models and then explore the books if they want to go deeper!