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Asmita Poddar's Projects

autoencoder-atlas icon autoencoder-atlas

Autoencoder-ATLAS: codes for implementation of autoencoder-decoder network to compress the data from the ATLAS experiments from 4 to 3 variables, and reconstruct the compressed data.

bayessentinel icon bayessentinel

Creating package for simulation and classification of multi-dimensional spectroscopic data taken from Sentinel-2 satellite covering the area of France

co-attention icon co-attention

Pytorch implementation of "Dynamic Coattention Networks For Question Answering"

deep-learning-dna-sequences icon deep-learning-dna-sequences

Deep learning for identifying important motifs in DNA sequences. Exploration of the structure of the human genome by training neural network architectures (CNN, LSTM, Attention).

iclr15 icon iclr15

Sentiment Analysis with Ensemble

kaggle-electricity-prediction-eeml2019 icon kaggle-electricity-prediction-eeml2019

Data Analysis of Electricity Production and Consumption data of Romania over 9 years as a part of the EEML 2019 Data Analysis Challenge for Artificial Intelligence for Social Good

question-answering-squad2.0-dcn icon question-answering-squad2.0-dcn

Implementation of a Dynamic Coattention Network proposed by Xiong et al.(2017) for Question Answering, learning to find answers spans in a document, given a question, using the Stanford Question Answering Dataset (SQuAD2.0).

reversible-digtal-watermarking icon reversible-digtal-watermarking

Coded in C++ using OpenCV to achieve colour space transformation from RGB to YCoCg in order to increase embedding capacity, and then watermark extraction, so that both watermark and cover medium remain unchanged.

tensorflow icon tensorflow

An Open Source Machine Learning Framework for Everyone

twitter-sentiment-analysis-r icon twitter-sentiment-analysis-r

Takes feeds from Twitter into R and the sentiment of the tweets is analysed and classified into positive, negative and neutral tweets.

uncertainty-estimation-diabeticretinopathy icon uncertainty-estimation-diabeticretinopathy

Estimating uncertainty of neural networks for automated screening of Diabetic Retinopathy using the PyTorch framework. Generated visual explanation of the deep learning system to convey the pixels in the image that influences its decision Integrated Gradient method.

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