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permalink: /Projects/
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# Projects
## Classification of Multilingual Disaster Tweets
<small>WISOC Lab,  August - November 2017</small>
<p>Worked on Crisis Tweet classification with respect to 2015 Nepal Earthquake.
The task involved identification of multilingual tweets that request help and those
that provide aid. Tweets from victims seeking help were identified and matched
with tweets providing suitable help. [Published at FIRE, 2017](http://ceur-ws.org/Vol-2036/T2-3.pdf) .</p>

## Fake News Detection
<small> Information Retrieval Course Project, October - November, 2017 </small>
<p>Fake News and it's proliferation is a massive problem in our society. We trained a deep neural network to classify news articles into fake and real. We used Kaggle Fake News dataset along with News from established media houses. We got over 90% accuracy. 
Further we created a smaller dataset with data from Indian media houses. We got similar results in this dataset too. [Project Repo](https://github.com/atalukdar/FakeNewsDetector)</p>
## Concurrent Data Structures
<small> Under Prof S. Balasubramanian , BITS Pilani , August 2017 - December 2017
</small>
<p>
Analysis and optimisation of concurrent algorithms as a semester long project under Prof Balasubramaniam. Till date have implemented bloom filters, priority queues and skip list and improved their scalability.
</p>

## Arrhythmia Detection From ECG signals 
<small> Under Dr. <NAME>, Calcutta University, July 2017 - August 2017
</small>

<p>Created Neural Network based classifier to identify and identify and classify arrhythmia from ECG using MIT-BIH Arrhythmia Database - PhysioNet. LSTM architecture was used in this classifier.
</p>

## Classification of Multilingual Disaster Tweets
<small>WEBEL, Summer 2017</small>
<p>Developed  a bio-metric attendance system through Facial Recognition using
VGG-16 network architecture.[Project Repo](https://github.com/atalukdar/facial_recognition) .</p>

## Digital Alarm System using 8086 Micro-Processor
<small>April 2017</small>

<p>Designed a hardware system on Proteus to simulate the working of a digital alarm clock with LCD Display using an 8086 Micro-Processor for a course. An assembly script was used to run the model. Find more details of the project <a href="https://github.com/atalukdar/MUPI_digital_clock">here</a>.</p>

## MNIST in Python
<small>Under Dr <NAME>, WISOC Lab,  March 2017</small>

<p>Created a library using Numpy that implemented all basic deep learning functionality in python. Used this library to to perform classification task on the popular MNIST dataset for recognition of handwritten digits. This library was developed for teaching students the nuts and bolts of neural networks.
<a href ="https://github.com/atalukdar/MNISTinPython">Find it here.</a></p>

## Nearest Available Hospital Locator Application 
<small>Apogee 2016 Application
</small>
<p>
Developed an Android Platform based Application that provides the user with the nearest hospitals from his/her location that have the required medical facilities available at that moment. Hospitals will update their database of the different types of beds available and availability of other medical facilities (e.g.: ventilators, operation theatres, etc) real-time. This application would provide the user with the necessary information. It was supported by backend in Django framework.
</p>


## Checkmate 2016 Pokemon-Go!
<small>Development Period: July 2016 - Aug 2016 </small><br>

<p>Checkmate is BITS Pilani's revolutionary quizzing event, where the participant's aptitude for analytical thinking and logic based problem solving is put to test. Hosted on a web based platform, it is conducted by the chapter in the fall semester of every academic year. The theme idea for September 2016 Checkmate was derived from the then popular game version japanese anime, POKEMON.</p>

<p>Find the complete code of the event <a href="https://github.com/jbnerd/Pokemon-Checkmate-2016">here</a>. For more details of this project, click <a href="/projects/Checkmate_2016_pokemon_go/">here</a>.</p>


<commit_msg>Updates<commit_after>---
layout: archive
permalink: /Projects/
author_profile: true
---

{{ page.excerpt | markdownify }}

# Projects
## Classification of Multilingual Disaster Tweets
<small>WISOC Lab,  August - November 2017</small>
<p>Worked on Crisis Tweet classification with respect to 2015 Nepal Earthquake.
The task involved identification of multilingual tweets that request help and those
that provide aid. Tweets from victims seeking help were identified and matched
with tweets providing suitable help. <a href ="http://ceur-ws.org/Vol-2036/T2-3.pdf"> *Published at FIRE, 2017*</a> .</p>

## Fake News Detection
<small> Information Retrieval Course Project, October - November, 2017 </small>
<p>Fake News and it's proliferation is a massive problem in our society. We trained a deep neural network to classify news articles into fake and real. We used Kaggle Fake News dataset along with News from established media houses. We got over 90% accuracy. 
Further we created a smaller dataset with data from Indian media houses. We got similar results in this dataset too.
<a href ="https://github.com/atalukdar/FakeNewsDetector"> *Project Repo* </a></p>
## Concurrent Data Structures
<small> Under Prof S. Balasubramanian , B<NAME> , August 2017 - December 2017
</small>
<p>
Analysis and optimisation of concurrent algorithms as a semester long project under Prof Balasubramaniam. Till date have implemented bloom filters, priority queues and skip list and improved their scalability.
</p>
## Arrhythmia Detection From ECG signals 
<small> Under Dr. <NAME>, Calcutta University, July 2017 - August 2017
</small>

<p>Created Neural Network based classifier to identify and identify and classify arrhythmia from ECG using MIT-BIH Arrhythmia Database - PhysioNet. LSTM architecture was used in this classifier.
</p>

## Classification of Multilingual Disaster Tweets
<small>WEBEL, Summer 2017</small>
<p>Developed  a bio-metric attendance system through Facial Recognition using
VGG-16 network architecture.<a href ="https://github.com/atalukdar/facial_recognition">*Project Repo*</a></p>

## Digital Alarm System using 8086 Micro-Processor
<small>April 2017</small>

<p>Designed a hardware system on Proteus to simulate the working of a digital alarm clock with LCD Display using an 8086 Micro-Processor for a course. An assembly script was used to run the model. Find more details of the project <a href="https://github.com/atalukdar/MUPI_digital_clock">here</a>.</p>

## MNIST in Python
<small>Under Dr <NAME>, WISOC Lab,  March 2017</small>

<p>Created a library using Numpy that implemented all basic deep learning functionality in python. Used this library to to perform classification task on the popular MNIST dataset for recognition of handwritten digits. This library was developed for teaching students the nuts and bolts of neural networks.
<a href ="https://github.com/atalukdar/MNISTinPython">Find it here.</a></p>

## Nearest Available Hospital Locator Application 
<small>Apogee 2016 Application
</small>
<p>
Developed an Android Platform based Application that provides the user with the nearest hospitals from his/her location that have the required medical facilities available at that moment. Hospitals will update their database of the different types of beds available and availability of other medical facilities (e.g.: ventilators, operation theatres, etc) real-time. This application would provide the user with the necessary information. It was supported by backend in Django framework.
</p>


## Checkmate 2016 Pokemon-Go!
<small>Development Period: July 2016 - Aug 2016 </small><br>

<p>Checkmate is BITS Pilani's revolutionary quizzing event, where the participant's aptitude for analytical thinking and logic based problem solving is put to test. Hosted on a web based platform, it is conducted by the chapter in the fall semester of every academic year. The theme idea for September 2016 Checkmate was derived from the then popular game version japanese anime, POKEMON.</p>

<p>Find the complete code of the event <a href="https://github.com/jbnerd/Pokemon-Checkmate-2016">here</a>. For more details of this project, click <a href="/projects/Checkmate_2016_pokemon_go/">here</a>.</p>



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