This repository contains code for predicting Score of IPL and analysing different players. Developed using Flask and python. Website is hosted on heroku.
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Updated
Aug 14, 2020 - HTML
This repository contains code for predicting Score of IPL and analysing different players. Developed using Flask and python. Website is hosted on heroku.
Reproduction package of the paper "Mitigating Data Imbalance for Software Vulnerability Assessment: Does Data Augmentation Help?" in The International Symposium on Empirical Software Engineering and Measurement (ESEM) 2024
This project aims to provide an advanced and dynamic system for predicting stock prices and monitoring their movements in real-time. Utilizing various machine learning techniques and technical indicators, this system continuously updates itself with the latest stock market data and retrains its predictive models to ensure accuracy.
A simple python program that implements linear regression model
This project aims to develop a machine learning model to predict bike-sharing demand based on various factors such as weather conditions, time of day, and historical usage patterns. The dataset used for this project consists of 8760 records and 14 attributes.
AI/ML mini Project repo
Scrapping and Sentiments Analysis of Covid-19 data. This reserach show case the webscraping of COVID-19 Subvariant XBB.1.5 through twitter API. Secondly Sentiments analysis was carried out to check people's emotion on the variant of the COVID. form my analysis it was shown that people show or have more positive sentiments towards the virus .
MIT Deep Learning Book by Ian Goodfellow, Yoshua Bengio and Aaron Courville. in PDF format (complete)
AI Mental Fitness Tracker Project
A machine learning model for predicting diabetes risk using key health indicators. The project involves data preprocessing, model development with TensorFlow and scikit-learn, and evaluation to achieve accurate predictions.
This project uses machine learning to predict whether a loan applicant will repay their loan. The project uses a dataset of historical loan data from PeerLoanKart, a peer-to-peer lending platform.
This project consists of a ML model that predicts the price trend of food crops in Tanzania especially Maize, Rice and Beans
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