Yash Saini (yash-saini)

yash-saini

Geek Repo

Company:Univeristy at Buffalo

Location:Buffalo

Home Page:https://www.linkedin.com/in/yash-saini/

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Yash Saini's repositories

Emotion-analysis-of-Tweets-from-top-3-colleges-of-the-world.

The project caters to finding the 5 sentiment scores (Happiness,Fear,Anger, Disgust,Sadness) of each tweet using a described formula.

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Sentiment-Analysis-

The project 'Sentiment Analysis of top colleges in India using Twitter Data', extracts tweets from the twitter , preprocesses them , assigns sentiment scores and then using different ML techniques , their accuracies are compared.

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LSTM

The following code depicts text generation using LSTM. The dataset used is Shakespeare's Macbeth. 50 characters are taken and 51st character is predicted using this model. 1 epoch cycle with 0.1 million entries fed to train the network.

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Project-on-HR-analytics

This project makes use of various ensemble learning techniques for example bagging, boosting ,gradient boosting machine and extreme gradient boosting machine on an HR dataset attached herewith. The measures of performance for each technique is calculated.

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Stock-trends-prediction-using-RNN

RNN is used here to predict the trends using historical stock data obtained through yahoo finance

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UB_Course

This repository caters to having reviews of various Master's level courses currently (fall 2022 onwards) taught at the University at Buffalo (State University of New York)

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Hate-Speech-Analysis

This research deals with analyzing the hate speech with a novel method of combining LDA with SOM. Experimentally no of topics derived from the dataset after the application of LDA was 10. Dominant topic was calculated for each data value. This data was fed to a SOM network initially assigned with random weights. The learning rate for SOM was 0.5 and number of iterations were 100. The clusters were formed as a result and the map was displayed.

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Project-on-Cancer-detection-

The project is based on using supervised machine learning techniques (KNN,SVM and xgboost) on wisconsin dataset of breast cancer, the accuracy and other metrics of the techniques are pit against each other.

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Python-stock-market-analysis

The project analyzes the stocks of three major car companies , compares them , plots graphs and calculates returns & cumulative returns on them.

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text_editor

TextChanger is a reactjs app which caters to performing various functionalities such as conversion of a text to Uppercase, Lowercase, counting vowels and consonants, reading the input text aloud and stopping it, clearing the input text, displaying the preview, and counting the words and characters.

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Tidings_Today

This application built on React.js displays various news articles fetched from News API website. The application hosts several features namely Dark Mode/ Various news categories/ Next and previous buttons/ About section / Loading spinner/ Loading bar / news-items cards.

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Autoencoders-movie-recommender-system

As per the Deep learning course A-Z , a movie recommender system was created for the MovieLens dataset.

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Cloud_Notebook

This application caters to building a full stack application depicting the features of snippets of notes saved to the cloud.

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Cloud_notebook_backend

This project contains the backend work of the cloud_notebook

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Image_Augmentation

This repository contains the jupyter notebook catering to demonstrating the image augmentation techniques using pytorch.

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junction

Junction is a software to manage proposals, reviews, schedule, feedback during conference.

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lidar_super_resolution

Simulation-based Lidar Super-resolution for Ground Vehicles

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Python

All Algorithms implemented in Python

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Python_Programes

The repository contains some of the Python Programs

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Reactjs_tips_tricks

This repository caters to discussing about various tips and tricks which could be applied on any react project. Discussions revolve around essential react concepts and their practical applications

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yash-saini

Introduction

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