@ericyocam6Professor, California Polytechnic State University
Shipped: Machine Learning Portfolio — Hands-On AI Experiments
An open-source machine learning portfolio providing hands-on educational experiments in AI model development.
The repository includes a Keras regression notebook demonstrating a practical machine learning workflow through executable Python code.
Designed for students, educators, and developers interested in exploring machine learning concepts, model development, and experimentation.
The project is an educational proof of concept rather than a production-ready AI application.
Machine LearningArtificial IntelligenceDeep LearningKeras
PythonRegressionAI EducationJupyter Notebook
Comments2
Has a class at Cal Poly worked through the notebook yet? Share one or two things your students said after running it, like where they got stuck or what finally clicked, because that will tell another professor faster than the description whether it fits their course.
Great suggestion, Ryan! I haven't used this particular notebook as a formal classroom assignment at Cal Poly yet, so I don't have specific student feedback to share. However, it could be a useful hands-on exercise for introducing neural network regression, model training, and performance evaluation. I agree that documenting where students encounter difficulties and what concepts become clearer through experimentation would help other instructors determine whether it fits their courses. Appreciate the suggestion!
2 comments
Has a class at Cal Poly worked through the notebook yet? Share one or two things your students said after running it, like where they got stuck or what finally clicked, because that will tell another professor faster than the description whether it fits their course.
Great suggestion, Ryan! I haven't used this particular notebook as a formal classroom assignment at Cal Poly yet, so I don't have specific student feedback to share. However, it could be a useful hands-on exercise for introducing neural network regression, model training, and performance evaluation. I agree that documenting where students encounter difficulties and what concepts become clearer through experimentation would help other instructors determine whether it fits their courses. Appreciate the suggestion!