Given module calculates the minimum cost of the spanning tree for a graph using Kruskal's algorithm. The graph is implemented by edge list and disjoint set union in Python.
Implementation of most famous clustering algorithm(K-means) using Expectation(E)-Maximization(M) technique in Python using NumPy.
Implementation of Linear Regression from scratch in Python using NumPy library with mean squared error as loss function.
Given code packet do preprocessing like removing useless and less frequent words present in text data, vectorizing text and creating Embedding matrix (as NumPy array) in Python.