Discover NamrataThakur/Human-Activity-Recognition Open Source project

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Created almost 4 years ago
Updated about 1 year ago

NamrataThakur

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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.

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.

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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.

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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.

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Market-Basket-Analysis-and-Recommendation

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Singapore-Advisor

Detailed sentiment analysis (overall and aspect based sentiment analysis) on major Singapore attractions.

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Price-Optimization-Project

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NamrataThakur/Human-Activity-Recognition

NamrataThakur

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