Machine Learning Model for Order Demand Prediction based on historical Order data - Built for Swiggy Hackathon 2018
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Updated
Jul 16, 2018 - Python
Machine Learning Model for Order Demand Prediction based on historical Order data - Built for Swiggy Hackathon 2018
In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).
This repository contains Python functions for predicting time series.
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
The project would generate report of the result of the students and is also capable of concluding the result analysis report of the students as in tables, figures in Excel Sheet. The project is based on python which will use the web scraping technique used to launch the website from an automated software (as a web browser) to visit the website (…
Time series processing library
A simple implementation of Random Forest Regression in python.
Machine Learning Prediction Software Based on Classification and Regression Based on Processor [CPU] Specifications
Machine learning algorithm solves multi-class classification problem of video games content rating (without playing it). Quantitative Methods for Computer Science exam project.
This repository is a collection of both basic and advanced code templates for Model Building. All codes I am sharing are from the practical exercises I did from the Data Science Infinity Program.
Project aims to forecast potato prices in India using LSTM, KNN, and Random Forest Regression, integrating historical data on prices, regional stats, and rainfall patterns. Targeting agricultural stakeholders for informed decision-making.
Scripts for the paper "Application of machine learning regression models to inverse eigenvalue problems". Authors Nikolaos Pallikarakis and Andreas Ntargaras. Correspondence at [email protected].
This repository enables an engineer to generate predictions for the mechanical bending performance of corroded beams, using a database of 725 corroded beams tested under monotonic bending. Outputs include the maximum bending moment, residual capacity percentage, yield load, yield displacement, and ultimate displacement.
Mon Travail à Initiative Personnelle Encadré (TIPE) sur le thème de la ville pour mon parcourt en MP.
A machine learning method for confidence interval (CI) computation with specific application to Covid-19 forecast on 54 countries.
House-Price-Prediction-App
it's my first data science application using streamlit and my first project uploaded to Github. I would like to thank Misra_Turp(youtube) for this project.
It was a competition on KAGGLE for prediction on the most sales products on bikes via their features
A Streamlit application for predicting house prices in California
Implementation of regression algorithms in python.
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