User:Rjain27

Repository Structure : 1) __dataSets__ - This folder contains the data sets used in training and testing machine learning models obtained from the CSC517 course at NCSU. 2) __src__ - The main logic is grouped into __1) data_preprocessing____2) data_analysis__ and __3) models__ directories. Further __Machine learning__ and __Neural Network__ models are divided into respective folders. 3) __test__ - This folder contains the tests corresponding to each of the files in the src directory. 4) __Results__ - This folder contains all the results obtained from the files in the src directory. 5) __bin__ - This folder contains the original files contributed by various others to the Peer_Logic Project.

Created Requirments.txt file by for dependency Management

Added README.md (is description for each and every file Required ?) Added utils module in each of the directory and abstracted the logic employed by multiple files in the directory. Refactored modules in the Traditional Machine Learning directory and Gabrieals, rashiks files and added them to the Repository. Studied Naive Bayes, Bayesian Networks, KNN and started with Deep Network.