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ANair's Projects

appliedmachinelearning icon appliedmachinelearning

This repository contains machine learning projects using the following algorithms implemented in Python - Decision Tree, Genetic algorithm, Linear Regression, Neural Network and Polynomial Fitting

correlation-between-social-media-and-stock-market icon correlation-between-social-media-and-stock-market

Certainly: This repository comprises the project code and related files exploring the correlation between social media activity and the stock market. Leveraging stock data sourced from Yahoo Finance and web-crawled social media articles, the project aims to uncover insights into the relationship between online discourse and stock market trends.

e4_pyhrv icon e4_pyhrv

Python toolbox for Heart Rate Variability

e4package_flirt icon e4package_flirt

FLIRT is a python package that processes wearable sensor data to obtain features

e4package_neurokit icon e4package_neurokit

NeuroKit2 is a python toolbox that aids in neurophysiological signal processing

fitbit_fitness_tracker icon fitbit_fitness_tracker

This is a repository for EDA on Fitbit users’ fitness dataset to gain insights into the users activity and overall health. Dataset is extracted from Kaggle.

machine_reading_comprehension icon machine_reading_comprehension

This repository contains the project done on Machine Reading Comprehension, using the Squad2 dataset, which is a benchmark data for question-answering.

machine_translation icon machine_translation

This repository consists of the files related to the Machine Translation project using Flores200 dataset to implement machine translation between two languages. The implemented models include seq2seq models like OPUS-MT, M2M-100 and MBART-50.

machinelearning icon machinelearning

This repository contains the implementations of basic machine learning algorithms using datasets from Kaggle and UCI Machine Learning Repository

python icon python

This repository contains the exercises used in the Python course

spiced icon spiced

Code for the paper "Modeling Information Change in Science Communication with Semantically Matched Paraphrases" from EMNLP 2022

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