Arushi Sharma (Arushi04)

Arushi04

Geek Repo

Company:Northeastern University

Location:Boston

Twitter:@arushi04_

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Arushi Sharma's repositories

Information-Retrieval

This repo contains mini projects in Information Retrieval. Covers indexing, document ranking, web crawling, page ranking, and evaluating different models

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character-level-RNN

This project trains a few thousand names from 18 languages of origin and predicts which language a name is based on the spelling. It uses a character-level LSTM model to predict the next character. The model reads words as a series of characters and outputs a prediction and a “hidden state” at each step, feeding its previous hidden state into each next step. We take the final prediction to be the output, i.e. which class the word belongs to.

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ImageClassification

This project explores image classification using PyTorch on the CIFAR10 dataset. The model has been trained using Convolutional Neural Network.

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Named-Entity-Recognition-on-Social-Media-Data

This project helps to identify the classes present in the unstructured text of social media and tags the tokens as person, location, group, creative-work, product and corporation.

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arushi04.github.io

:sparkles: Build a beautiful and simple website in literally minutes. Demo at https://beautifuljekyll.com

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COVID-19-Analysis

This project does analysis on confirmed, death, and recovered cases of COVID-19 across the world and predicts the death of patients. It also predicts the spread of covid-19 in USA using SIR model.

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Image-Segmentation-and-Clustering

Image Segmentation and clustering on handbag images to find color attributes for Handbags

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Digit-classification-MNIST

We will be doing multiclass classification using Pytorch

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Forecasting-Grocery-Sales

The project does exploratory data analysis and uses multiple forecasting models to forecast grocery sales for next 15 days for a grocery store.

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github-readme-stats

:zap: Dynamically generated stats for your github readmes

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handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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MachineLearning_CS229

Contains the implementation of ML algorithms

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R_projects

contains small projects in R

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Spam-Classification

Spam Classsification of Emails

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spring-cloud-task

Short lived microservices with Spring Batch

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