Python simple decision tree classifier

Decision tree code now has comments, explaining how the code works.

Code for a simple decision tree classifier has been added. This
is demonstrated to work with the classic iris dataset.

BFS

Created clean_text.py

bucket sort added

Added graphs python code

perceptron1.py

This is a single layer perceptron code.

This is a single layer perceptron code.

Depth First Traversal algorithm for a graph is implemented in Python. Driver code to test the same is also provided

I have added BFS implementation in python. Also the driver code is provided.

This is extension file of text preprocessing which is used to counter the words and to eliminate the Special chars , Upper Case letters

Added python script which demnostrates a graph data structure,
with some basic methods (operators).

Added BFS

Add Jump Search

Create Dijkstra.py

Added Basic Neural Network

Add heapsort

Added space at end of file + at another return

Corrected some of the function docs.

Adjusted the spacing of the functions to be more PEP friendly.

A script demonstrating heapsort using a max heap has been added.
Comments have been added, describing the steps.

contains an implementation of dijkstra for adjacency matrix representation of graph and the driver code to run it.

Basic implimentation of a CNN using pytorch.
1 converlutional layer:
-> input depth 3
-> output depth 16
-> kernel size 3
-> padding 1

1 maxpool layer

This is a basic implementation of a neural network using pytorch. The network accepts an input of 784 and generate a final output of 10. eg(classifying 28x28 -> 784 images of 10 digits)

Perceptron algorithm