This repo eontaints course materials, resources, personal notes and assignments done for for SWE 343/344.
Problem Set 01:
The dataset consists of 5,863 JPEG X-Ray images categorized into two types (Pneumonia and Normal), organized into three folders: train, test, and val. Each folder contains subfolders for each image type.
These chest X-ray images (anterior-posterior view) were obtained from pediatric patients aged one to five years at a renowned hospital. The X-rays were part of the routine clinical care for these patients.
As a data scientist in the healthcare industry, your task is to develop a Convolutional Neural Network (CNN) model capable of classifying medical images into their respective categories. The model should accurately identify the type of medical image shown in an image based on the image itself.
Dataset:
Problem Set 02:
A banking institution aims to create a model predicting whether a customer will subscribe to a term deposit based on their banking behavior. They have collected a dataset of past customers, including information about demographics, account details, and subscription status. The bank intends to use Logistic Regression to predict whether a new customer will subscribe to a term deposit based on their banking behavior.
The dataset for this problem statement is the "Bank Marketing Data Set," containing information on bank customers. The dataset includes 17 attributes such as customer demographics, account details, and subscription status. Each customer is classified as either yes or no based on whether they subscribed to a term deposit or not.
Dataset: