Education

I studied at South Point High school (Calcutta) and completed my secondary and higher secondary educations here. Thereby, I did my Bachelor's degree in Computer Science and Engineering from Kalinga Institute of Industrial Technology (Bhubaneswar).

Final Grades:

What I know

Certifications:

How I learn

I am mostly self-taught and like to learn by building new stuff and reverse engineering ideas.

Experience

I worked at Accenture from June 2019 to August 2020 on a Japanese implementation project, where my main focus was on data migration tasks and building tools to support identification and filtering of errors during mass data upload, and implementing tools to create Work Breakdown Structures.

Projects

A simple dashboard application to track covid-19 cases around the world. The application data are fetched through public APIs and thereby stored in local databases, which are then used to render a local API through which the data is imported into the various views and tables.

Technologies used:

• 1. Django- Web Framework (for entire backend)


• 2. Chart.js (Javascript) for front end charts


• 3. Datatables (Jquery) for rendering the details in the table


• 5. HTML and CSS (for frontend)


• 6. Finally hosted on heroku

A simple chat room application which can allow multiple users to chat

• 1. SocketIO


• 2. NodeJS (for entire backend)


• 3. ExpressJS


• 4. HTML and CSS (for frontend)


• 5. Finally hosted on heroku

Minor Projects (not live)

Web Crawler

Simple web crawler using multi-threading built to understand how web crawling / spiders work in general along with understanding the application of multi-threading in python

Blogging website

A basic blogging website built to understand the working principles of django.

Customer Segments

Using unsupervised learning techniques to see improve the delivery plan of a wholesale distributer which was recently changed and was generating loss rather than making any profit. The customers need to be segmented into distinct segments so that individual segments can be accessed in a more efficient way.

Enron K-Means Mini Project

In this project a K-Means clustering algorithm is used on the Enron Email Corpus Dataset and related financial data and is finally used to build a Machine Learning Algorithm able to identify persons of interest (POI) in the Enron Scandal.

Finding Donors

Using machine learning algorithms to find the candidates who are likely to donate for a charity organization.

Spam Detection

Classifying whether a message is a spam or not using Naive Bayes Classifier.

Data Analytics Nanodegee Projects

Exploring weather trends

Exploring the weather trends of a particular location using generic excel tools and presenting a report on how the weather has been changing according to the global weather trends for the past few decades.

Investigate a dataset

In this project an analysis of a movie dataset was made to identify some priority questions like what are the factors which help a movie be considered as a "popular choice", who are the most popular actors, what is the average runtime of the movies and how much average profit was made by the movies throughout the years.

Analyse AB-Test results

Here, an analysis was made on the results of a AB-test of a particular feature of a website to identify whether the changes introduced in the website was feasible enough to be pushed finally.

We Rage Dogs (Twitter Data extraction)

Here an analysis was made after extracting data (like tweet informations) of a particular twitter account and showing the popularity of the dogs based on the ratings provided along with some other informations.

Titanic Dataset - Exploration and Visualization

Here an analysis is done of the tragic titanic event of 1912. An analysis was done to look at what could be the features which help us understand whether a person on board as likely to survive or not. The related visualizations were provided to help support every idea.