Detection of COVID-19 induced Pneumonia using Chest X-rays - A Deep Learning Implementation.
An approach to distinguish between NORMAL, PNEUMONIA, and COVID-19 positive patients using Convolutional Neural Networks for Image classification on Chest X-rays.
The links to the pre-processed data sets are provided below:
Download COVID-19 Dataset
Download NORMAL and PNEUMONIA Dataset
Exploratory Data Analysis and Data Extraction (Notebook)
Binary Classification (COVID vs NORMAL)
Multi-Class Classification (COVID vs PNEUMONIA vs NORMAL)
*CXR - Chest X-rays
*PA - Posteroanterior (view of X-ray images)
Big Data Wrangling with Google Book Ngrams
(Load, filter, and visualize a large dataset in AWS cloud environment)
Work with real-world data using Hadoop, Spark, and the AWS S3 filesystem.
Pull data from (public) S3 bucket to HDFS (Hadoop)
Analyze and filter data using Spark
Perform Data Analysis and visualizations.
Hotel Reviews - Booking.com
(Natural Language Processing/ Sentiment Analysis)
Download the Dataset
Exploratory Data Analysis and Data Wrangling
Employ various ML models and comparing their performance (Logistic Regression with PCA and Cross-Validation, KNN, Decision Trees and Random Forests)
US Presidential Elections
(EDA, Data Cleaning, Visualization, Statistical modeling, and inference)
EDA and Data cleaning on previous election data.
Statistical modeling, Model selection, and Inference
BIXI Montréal, bike-sharing system (Data Analysis and Data Visualization)
Data Analysis of the real-world data using SQL queries on MySQL workbench.
Data Visualization and Dashboards on Tableau with key insights into revenue and business growth.