Matta Rithvik (20481A05F0)

20481A05F0

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Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning

This is a project on "Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning" using Pytorch, python, deep learning, gru, plotly

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react-schedule-app

My cricket team's match schedule

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NBA-Data-Mining

Sports analytics project using NBA data to explore how individual player statistics predict overall team success.

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SRGAN

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

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Deep_SESR

Simultaneous Enhancement and Super-Resolution. #RSS2020

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Book_Recommendation_System

In this project we are provided with three datasets, one contains information about users and the other two contains the information about the books they choose and the ratings given by them to the books.

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Book-Stock-Exchange

Book Recommendation System - ML Project

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Books-Recommendation-System

This is a Recommedation System based project where Top 5 books will be recommended to a user.

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VTU-CSE-LAB-SOLUTIONS

ONE PLATFORM FOR ALL THE CSE LAB SOLUTIONS OF VTU - EASIEST, SIMPLE & CRYSTAL CLEAR CONTENT :) (SCHEMES INCLUDED ARE +2015 +2017 +2018)

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Final-Year-Machine-Learning-Stock-Price-Prediction-Project

Final Year B.tech Project on Machine Learning Stock Prediction through Deep Learning

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Predicting-Consumer-Purchase-intention-using-Twitter-Data

Predicting Consumer Purchase intention using Twitter Data

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diabetic-retinopathy

A Django application developped for classification of a diabetes complication that affects eyes

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Third-Eye-Final-Year-Project

Forensic Face Sketch Construction and Recognition (My B.E. Final Year Project)

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Speech-Separation

Final Year Project for Speech Separation

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Health-Care-Chatbot

It is a medical chatbot that will provide quick answers to FAQs by setting up rule-based keyword chatbots.

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data

Data Sets for Machine Learning Practice

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2020_CSE_14

Final Year VTU Project

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Forecasting-sales-of-Walmart-retail-goods

Note: This is one of the two complementary competitions that together comprise the M5 forecasting challenge. Can you estimate, as precisely as possible, the point forecasts of the unit sales of various products sold in the USA by Walmart? If you are interested in estimating the uncertainty distribution of the realized values of the same series, be sure to check out its companion competition How much camping gear will one store sell each month in a year? To the uninitiated, calculating sales at this level may seem as difficult as predicting the weather. Both types of forecasting rely on science and historical data. While a wrong weather forecast may result in you carrying around an umbrella on a sunny day, inaccurate business forecasts could result in actual or opportunity losses. In this competition, in addition to traditional forecasting methods you’re also challenged to use machine learning to improve forecast accuracy. The Makridakis Open Forecasting Center (MOFC) at the University of Nicosia conducts cutting-edge forecasting research and provides business forecast training. It helps companies achieve accurate predictions, estimate the levels of uncertainty, avoiding costly mistakes, and apply best forecasting practices. The MOFC is well known for its Makridakis Competitions, the first of which ran in the 1980s. In this competition, the fifth iteration, you will use hierarchical sales data from Walmart, the world’s largest company by revenue, to forecast daily sales for the next 28 days. The data, covers stores in three US States (California, Texas, and Wisconsin) and includes item level, department, product categories, and store details. In addition, it has explanatory variables such as price, promotions, day of the week, and special events. Together, this robust dataset can be used to improve forecasting accuracy. If successful, your work will continue to advance the theory and practice of forecasting. The methods used can be applied in various business areas, such as setting up appropriate inventory or service levels. Through its business support and training, the MOFC will help distribute the tools and knowledge so others can achieve more accurate and better calibrated forecasts, reduce waste and be able to appreciate uncertainty and its risk implications. Acknowledgements Additional thanks go to other partner organizations and prize sponsors, National Technical University of Athens (NTUA), INSEAD, Google, Uber and IIF.

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SalesPredictions

Forecasts Walmart sales based on weather data.

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super-resolution

Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution

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image-super-resolution

TensorFlow2 implementation of SRResNet and SRGAN

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Python

All Algorithms implemented in Python

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rajaprerak.github.io

Personal Portfolio Website

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Blood-Bank-And-Donation-Management-System

An Online System built for the Blood Donation Organisation to manage the Blood Bank System in which Blood Donors can willingly give their name and the Person in need of blood can find whether the Blood is available or not.

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standard-algorithms

Implementation of standard algorithms

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StateSpaceModels.jl

StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.

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Covid_time_series

A machine learning project analysing and forecasting Covid cases using time series methods.

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covid-19-data

Data on COVID-19 (coronavirus) cases, deaths, hospitalizations, tests • All countries • Updated daily by Our World in Data

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magictools

:video_game: :pencil: A list of Game Development resources to make magic happen.

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