Homework 4:

Team members: Mousaalreza Dastmard - Francesco Pezone - Sri vaishnavi Reddy

Goals of this assignment are:

1. Bloom filter using hashing to make faster the procedure of checking an element is already exit in a set.
2. Alphabetical sorting using counting sort as it's core.
3. Implementing K-means
4. Drawback of K-means when it takes too much time

The repository includes the following files:

1. main.ipynb:

   A Jupyter notebook which provides an overview of every single step of which the process to implement the code has consisted in.

2. hashing_lib.py:

   A Python file which contains the code about hashing and bloom filter and finding the true false positives.

3. sorting_lib.py:

   A Python file which has all the functions needed for alphabetical sorting and analysing empirical running time.

4. clustring_lib.py:

   A Python file containing the code needed to implement K-means on given data.

5. theoretical_lib.py:

   A Python file with all are needed to check the K-means cons and the posibility of trapping in local minimum.