Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning

  • • Implemented the paper with the same title as the title of this project. The main aim of the project was to learn data science techniques to visualize data. Apart from the visualizations in the paper, two more visualizations were added to get more insights and to explore relationships and patterns in data.
  • The frontend was developed using HTML, Bootstrap, CSS, JavaScript, and D3js was used for data manipulation and to visualize data. Backend had a novel algorithm “ccPCA” which is a variant of PCA and is used to contrast clusters. The backend was implemented in Python and the whole project was hosted on Flask server.

Cloud Computing: Platform-as-a-Service

  • A Flask-based Web App designed to exemplify the power of PaasS platform by deploying this scalable application on Google App Engine. It uses GAE, Microsoft Speaker Recognition API, Google Speech-to-Text API and Cloud Firestore.

Histopathological Cancerous Cell Detection

  • I worked on a Machine Learning project to detect cells with cancerous symptoms. Implemented Deep Neural Network algorithms VGG-16, VGG-19, ResNet and CNN. I made 16 variants of these algorithms with varying architecture and the algorithms had an accuracy to detect cancer between 52% to 97%.

Foundations of Algorithms - Final Project

Implementation of two algorithms for the final project of Fundamentals of Algorithms subject. The algorithms were:

  • Budget Constrained Relay Node Placement with Minimum Number of Connected Components (BCRP-MNCC)
  • Identifying Codes

Fox Game

  • Developed a game using Vanilla JS, HTML and CSS

Blog Web Application [React + Firebase]

  • Project demonstrating a web application to manage blogs. This project demonstrates how to integrate a React Web Application and integrate it with Google Firebase to make an application that ensures realtime updates and employs a serverless architecture.

VueJS 2 Deep-dive

  • A complete deep-dive into VueJS from scratch. Contains content and code from very basic concepts of VueJS to complex VueJS features like Vuex and Vue Router.

NodeJS Deep-dive

  • A complete deep-dive into Node.js from scratch. Contains content and code from very basic concepts of Node.js to complex Node.js features like Express framework, MVC Architecture, Routing. Also contains content on making RESTful and GraphQL APIs.

Edge Computing [AWS + Raspberry PI]

  • Implemented an autoscaling project that allowed edge computing on Raspberry PI (IoT device) which allowed object detection. Used darknet to perform object detection. The autoscaling was done using our code and not using Amazon’s Elastic Load Balancer.
  • The traffic was directed to Amazon EC2 instances, which were directly scaled up and scaled down based on the number of requests waiting in the Amazon SQS queue. All the object detection results were then stored in Amazon S3 buckets.

Analysis of Geospatial Data

  • Performed mining of geospatial data in Phase 1 using Hadoop and HDFS. In Phase 2 I used Apache Spark and an extension of it that is used to manipulate and mine the geo-spatial data “GeoSpark” to find the “Hot zones of NYC Taxi” which shows at which locations are these taxis available and “Hot cells” which had geo locations with most number of taxis at a given point in time using Getis-Ord Statistics. The code was written solely in Scala.

L”Earn”

  • Implemented an interactive website that contains all the programming tutorials pertaining to my university’s curriculum. This was a personal project.
  • Front-end and back-end were developed using Java Server Pages (JSP), JAVA and database was managed using ORACLE 10g DBMS.