Namrata Thakur's repositories
Social-Network-Link-Prediction
A graph mining problem where the task was to predict a link between the given nodes. Engineered different features like Jaccard Distance, Cosine-Similarity, Shortest Path, Page Rank, Adar Index, HITS score and Kartz Centrality. Finally built non-linear models to get the final F1 score as 0.92.
Airbnb-New-User-Prediction
The problem that this case study is dealing with predicts the location that a user is most likely to book for the first time. The accurate prediction helps to decrease the average time required to book by sharing more personalized recommendations and also in better forecasting of the demand. We use the browser’s session data as well as the user’s demographic information that is provided to us to create features that help in solving the problem.
SIIM-PCR-Pneumothorax-Segmentation
This repository contains the image classification followed by semantic segmentation of Chest X-Rays to detect a clinical condition called Pneumothorax.
Human-Activity-Recognition
Implemented Divide and Conquer-Based 1D CNN approach that identifies the static and dynamic activities separately. The final stacked model gave an accuracy of 93% without the test data sharpening process.
Singapore-Advisor
Detailed sentiment analysis (overall and aspect based sentiment analysis) on major Singapore attractions.
SmartPortfolioAdvisor_Optimization-using-Genetic-Algorithm
IRS PM IS04FT Group 11 Smart Portfolio Advisor
Quora-Question-Pair-Similarity-Challenge
This challenge is about detecting the question when posted by the user on the Quora portal as duplicate or not .
Executive-PGP-in-ML-and-AI
This repository contains all my submissions for my graduate program at IIIT, Bangalore
MLP-and-CNN-on-MNIST-Dataset
In this repository, there are two python files having different Multi Layer Perceptrons (MLPs) and Convulational Neural Networks (CNNs) models built from scratch on the MNIST dataset.
PortfolioGA
Flask backend
Sentiment-Analysis-on-Amazon-Food-Review
This repository is doing sentiment analysis ( review analysis ) on Amazon Food Dataset