Dipankar Mazumdar, M.Sc 🥑

This project focuses on building an out-of-the-box Visualization chart 'Scatter-Pie plot' using Qlik Sense Extension API.
Technology stack: D3.js, Qlik Sense API's

The Project is an experimental work for developing a Full-stack Machine Learning solution using Plotly's Dash based on Python Flask. The goal was to use Python as the main programming language instead of Javascript to design a Dashboard for Cannabis dataset. This Visual Analytics solution leverages Machine Learning Algorithm(Random Forest) in the back-end to make predictions for the 3 type of Cannabis strains. A word embedding is also generated using the Gensim package. The tool also allows to… Show more

The Project is an experimental work for developing a Full-stack Machine Learning solution using Plotly's Dash based on Python Flask. The goal was to use Python as the main programming language instead of Javascript to design a Dashboard for Cannabis dataset. This Visual Analytics solution leverages Machine Learning Algorithm(Random Forest) in the back-end to make predictions for the 3 type of Cannabis strains. A word embedding is also generated using the Gensim package. The tool also allows to input any keyword related to the dataset and see the Top 5 similar words.

PS: The dashboard is a bit slow when it loads up initially since my Heroku dynamos are limited. So, kindly give it some time.

Visualization: Plotly
Machine Learning Algorithm: Random Forest
Framework: Flask
Programming Language: Python Show less

With the ever-increasing dimensionality of complex datasets, the ability to represent high dimensional data has always been a concern. Although there have been quite some advancements in the field of Visualization for the effective representation of a multidimensional dataset, problems like user interpretation and clutter-free representation contribute negatively to future usability. This project aims at addressing the aforementioned problems by proposing a radial visualization called RadViz… Show more

With the ever-increasing dimensionality of complex datasets, the ability to represent high dimensional data has always been a concern. Although there have been quite some advancements in the field of Visualization for the effective representation of a multidimensional dataset, problems like user interpretation and clutter-free representation contribute negatively to future usability. This project aims at addressing the aforementioned problems by proposing a radial visualization called RadViz. Radviz allows dimensions to be placed as anchors on the perimeter of a circle, thus allowing multidimensional datasets to be projected to low dimensional space. To allow for better user interpretability of a high -dimensional dataset, this project will use Machine Learning techniques in the backend and principles by two researchers Alexander et al. and Hyunwoo Han et al.

Technologies:
Python Flask framework
Backend: Machine Learning clustering algorithm
Visual Representations: D3.js Show less

The focus of this project is to develop an out-of-the-box Visualization object, Parallel Coordinate Plot(PCP) using Qlik's Open source solution, Nebula.js.

Technology stack: Nebula.js, D3.js, Qlik Sense SaaS.

The objective of the project is to classify multi-class Newspaper topics for the Reuter corpus dataset. In order to achieve so, the project has been primarily divided into 2 major components:
1. Feature engineering using Deep learning techniques
2. Building up a multi-layer Neural network to perform classification (LSTM).

Recent years has seen tremendous growth in the use of social media platforms by the people to voice their opinion about a variety of topics, which may lead to comments being ambiguous i.e. sometimes some comments might be misunderstood and may lead to conflict between the readers and the author. A similar kind of pattern has been seen when it comes to Newspaper headlines. We come across a lot of news headlines throughout the day and while some of them are very straightforward, some can be… Show more

Recent years has seen tremendous growth in the use of social media platforms by the people to voice their opinion about a variety of topics, which may lead to comments being ambiguous i.e. sometimes some comments might be misunderstood and may lead to conflict between the readers and the author. A similar kind of pattern has been seen when it comes to Newspaper headlines. We come across a lot of news headlines throughout the day and while some of them are very straightforward, some can be sarcastic in nature. This may seem offensive to certain groups of readers and result in misunderstanding the subtle nature of humor added to the headlines. Therefore there is a need to separate the headlines or comments based on their nature – sarcastic or non-sarcastic. The “Sarcasm Detector” system developed, helps to address this problem by providing an AutoML UI to help any user irrespective of the field(technical or non-technical), bring in their comments or headlines and predict if its sarcastic or not. The system also helps a user to explore the Visual insights and have a hands-on experience with different types of classification models in Machine Learning. Show less

The Project develops a Cipher cracking system by taking a Hash value(Cipher text ) from User and searches for the password until it finds the actual password.
Languages used: JAVA.
Operating System: Windows Xp/ higher, Linux

It provides the facility of purchasing various categories of books online.

The website jeccse.in is a support site designed for the Computer Science and Engineering students of Jorhat Engineering College.

The purpose of this website is to help the C.S. students with all the required study materials for a particular semester. The course materials are presented in the form of e-books and video lectures by NPTEL.