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CS3-DS4002: Alzheimer’s Impairement Classification Case Study

This repository contains the study, deliverables, data, and reference materials necessary to complete the Case Study.

Important Information

The Prompt and Rubric are two PDF files listed in this repository to guide you in completing the case study.


Data

The necessary data is located in the "Alheimers-detection-1" folder. This folder includes:

  • Trained and Test Data: Data obtained from Roboflow for model training and testing.
  • Cleaned Data: An 80/20 data split in the new-train and new-test folders.
  • Technical Information: The folder also contains technical details and code, including a CNN model for classification.

Reference Materials

The "Materials" folder contains helpful resources related to:

  • Alzheimer's Disease: Contextual materials related to Alzheimer’s and Biogen’s mission.
  • CNN Classification Models: Tips and best practices for building and improving CNN models in PyTorch.
  • Transfer Learning with ResNet50: Guidance on using ResNet50 architecture for transfer learning in deep learning models.

Getting Started

To get started with the case study, please follow these steps:

  1. Download the Data: Access the Alheimers-detection-1 folder for all necessary data files.
  2. Review the Prompt and Rubric: These PDFs will help you understand the case study requirements.
  3. Use the Materials Folder: Refer to the materials for context, CNN tips, and transfer learning guidance.

Note: this is an adhoc situation and not affliated with Biogen technology

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