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Exam project in foundations of data science. It includes three main components: Sub-Numpy, a Python library mimicking Numpy functionalities; Hamming's Code, focusing on error detection and correction in data transmission; and Text Document Similarity, which explores various algorithms to assess textual similarities.

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Foundations of Data Science: Programming and Linear Algebra - Final Project

This repository contains the collaborative work for the final exam project for the course CDSCO1001U, taught by Professor Raghava Mukkamala at Copenhagen Business School, Denmark. Our project focuses on implementing foundational data science algorithms in Python and exploring their applications.

Project Overview

This project is structured to implement:

  • Sub-Numpy a subset of NumPy functionalities in pure Python.
  • Develop a Hamming code for error detection and correction.
  • Create a program for computing document similarity.

Code Structure

  • /snumppy - Contains the implementation of SNumPy (Sub-NumPy) class.
  • /hamming_code - Includes the encoder and decoder for Hamming's code.
  • /text_document_similarity - Houses the document similarity program.

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Exam project in foundations of data science. It includes three main components: Sub-Numpy, a Python library mimicking Numpy functionalities; Hamming's Code, focusing on error detection and correction in data transmission; and Text Document Similarity, which explores various algorithms to assess textual similarities.

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