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Python project for the Fundamentals of of Data Science class for the MSc. in Data Science at the Sapienza University of Rome. The main purpose of the project is practicing Computer Vision concepts and performing Closest Neighbors classification on an image dataset.

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Fundamental Methods for Data Science - Homework 1

This is a Github repository created to submit the first Homework of the Fundamental Methods for Data Science (FDS) course for the MSc. in Data Science at the Sapienza University of Rome.


What's inside this repository?

  1. README.md: A markdown file that explains the content of the repository.
  2. HW1.ipynb: A Jupyter Notebook file containing all the relevant exercises of the homework.
  3. assets: A folder that includes text files with data used on the HW1.ipynb notebook.
  4. images: A folder that includes images used on the HW1.ipynb notebook.
  5. model: A folder that includes model images used when performing Closest Neighbors classification on the HW1.ipynb notebook.
  6. query: A folder that includes query images used when performing Closest Neighbors classification on the HW1.ipynb notebook.
  7. .gitignore: A predetermined .gitignore file that tells Git which files or folders to ignore in a Python project.
  8. LICENSE: A file containing an MIT permissive license.

Authors:

MSc. in Data Science, Sapienza University of Rome

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Python project for the Fundamentals of of Data Science class for the MSc. in Data Science at the Sapienza University of Rome. The main purpose of the project is practicing Computer Vision concepts and performing Closest Neighbors classification on an image dataset.

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