Predicting IVF Outcomes

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During my second year as a master’s student, the data science bootcamp that I attended had a final project: to do something with the medical data of IVF patients. It is an open dataset that can be accessed by anyone. A team of three was assigned, but in the end, I was working alone. At that time, there was no Claude Code or ChatGPT that could help me process this dataset. The idea that I had was straightforward (I have to admit it was not creative): based on the dataset, can we predict the possibility of a couple having a child through IVF (In-Vitro Fertilization) when they input their medical records. Streamlit was used as the frontend for the user to input the data. I ran the AI model on Amazon SageMaker. The details can be seen here: https://github.com/harrybpm/plds_teamc.git . I have also been trying to revive the project, and it can be accessed here: https://ivf-predictor.harrybp.com/