This repository contains the semester projects that I completed during the MS Computer Science program. The structure of this repository   is given below. The names represent different topics related to Data Science and Machine Learning.

Projects completed under this area were of various nature.

R Projects: Different datasets were used to learn working in R. It includes reading the data, finding missing values and filling them, visualization of the data and other preprocessing techniques.

APACHE Modules: Different APACHE modules like Hadoop, HIVE and HBASE were installed and test. Later on Apache Spark was installed and different commands were tested. More information is given in report. I also made guidelines for the installation which were shared with the class to help them.

Fraud Detection: Fraud Detection dataset from Kaggle was used. Machine Learning libraries of Apache Spark was used.

In this area three datasets were used and three classification techniques were applied on each of the datasets. The classification techniques used are:
  1. Naive Bayes Classifier
  2. Rocchio Classifier
  3. kNN Classifier

Datasets used were the text datasets which are are taken from UCI website:
  1. DB World: https://archive.ics.uci.edu/ml/datasets/DBWorld+e-mails
  2. Legal Reports: https://archive.ics.uci.edu/ml/datasets/Legal+Case+Reports
  3. Sentence Classification: https://archive.ics.uci.edu/ml/datasets/Sentence+Classification

I have worked on different datasets including from "cars", "MNIST", "notMNIST" and "fashionMNIST". 

"cars" dataset was taken from UCI website. Naive Bayes classifier was applied to it and than compared the results with NB classifier of "Scikit" Library.

""notMNIST" dataset is taken from kaggle. 2-layer Neural Network was used for classification. notMNIST dataset was first converted into the MNIST format and than the classification was done. Project Report is attached for further information.

"fashionMNIST" was a group project and we applied three techniques on it which are kNN, Single Layer Neural Network AND Convolutional Neural Network. Project Report and presenation is attached for further information.

This folder contains the files from OpenCV Documentation page. I am trying to learn OpenCV and I have started with the OpenCV       documentation. I will add more OpenCV projects in this folder.