FarhanaTeli/Factors-Influencing-US-Home-Prices

Using publicly available data for the national factors that impact supply and demand of homes in US, build a data science model to study the effect of these variables on home prices.

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KwokHing/Regression-with-a-Crab-Age-Dataset

A light-weight Kaggle challenge to predict crabs' age

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Yogeshpvt/Sustainable-Energy-Consumption-Analysis

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sathwikkes/Movie-Recommender-System

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MafikengZ/Machine-Learning-Advanced-Regression

This project is focused on building an Advanced Linear Regression model measuring the load-shortfall-3h in Spain

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mendez-luisjose/Boston-House-Price-Prediction-with-Scikit-Learn-Streamlit-and-Deployed-with-Flask

Boston House Price Prediction with Scikit Learn, Streamlit and Deployed with Flask

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wellylin8916/Stock-Crash-Risk-on-XGBoost-Model

xgboost預測股價崩盤風險

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UjjwalDeepXCIX/End-to-End-Ml-Regression-Project

Math Score Predictor

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sarah-zhan/house_price_prediction

House Prices - Advanced Regression Techniques - Predict sales prices and practice feature engineering, RFs, and gradient boosting

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avijay24/Bike-Rental-Demand-Forecasting-using-AWS-SageMaker

Conducted thorough statistical data analysis to identify key factors affecting bike rentals by implementing & deploying an XGBoost model, sourced from AWS Elastic Container Registry.

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Juosorioca420/DiplomadoCienciaDatos

Asignaciones propuestas para el Diplomado de Ciencia de Datos de la Universidad Nacional. Como Proyecto se propone el desarrollo de un modelo de predicción para activos volatiles y la construcción de Portafolios diversificados de Markowitz.

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MezbanS/Mercedes-Benz-Greener-Manufacturing

Reduce the time that cars spend on the test bench. Work with a dataset representing different permutations of features in a Mercedes-Benz car to predict the time it takes to pass testing. Optimal algorithms will contribute to faster testing, resulting in lower carbon dioxide emissions without reducing Mercedes-Benz’s standards.

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Axik0/OIL

Multivariate oil production time series analysis with XGBoost and neural networks

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KalinNonchev/xgbexcel

Python package that converts an XGBRegressor model to an Excel formula expression.

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IssamLL/Wining-Solution-ENSIAS-AI-ML-Competition

This repository contains the winning solution for the Energy Consumption Prediction Kaggle competition, securing second place.

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shrutibalan4591/Store-Sale-Prediction

An end-to-end ML project, which aims at developing a regression model for the problem of predicting the sales of a given product, based on its properties like item category, weight, visibility, MRP, type of outlet the product is sold, size of the outlet etc.

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NatenaelTBekele/retail_sales_forecast

Forecast weekly sales from a particular department

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aayush1036/housing-rent-prediction

End to End Machine Learning Project along with deployment.

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Mfundo-debug/Bank_Customer_churn

Bank Customer Churn Prediction

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Collinjia/NLP-CLRP-Contest

Kaggle NLP competition : Rate the complexity of text using BERT

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MYoussef885/House_Price_Prediction

The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.

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ghanmi-hamza/Hyperparameter_Tuning_Using_Optuna

Xgboost Hyperparameter Tunning Using Optuna

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vineetpatel725/Supplement-Sales-Prediction

Forecast sales for 350+ supplement retail chain stores for next 2 months

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rmkjee1510/ML1_House_Price_Prediction

House Price Prediction

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aws-samples/amazon-sagemaker-xgboost-regression-model-monitor-and-alerting

How to train, deploy and monitor a XGBoost regression model in Amazon SageMaker and alert using AWS Lambda and Amazon SNS. SageMaker's Model Monitor will be used to monitor data quality drift using the Data Quality Monitor and regression metrics like MAE, MSE, RMSE and R2 using the Model Quality Monitor.

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Ola76/Dairy_Goods_Sales_Database

The Dairy Goods Sales Dataset provides a detailed and comprehensive collection of data related to dairy farms, dairy products, sales, and inventory management.

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Harish-or-Peter/Appliance-Energy-Prediction

Predicted residential energy consumption using Linear Regression, Random Forest, and XGBoost models. Random Forest showed best performance, offering insights into energy usage patterns. Code and results on GitHub for reference and optimization.

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Chandrakant817/Calories-Burned-Prediction

Calories-Burned-Prediction Using Machine Learning. (Regression Use Case)

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anirudhaangiras/Power-Plant-Output

This project utilizes various regression models, including Linear Regression, Decision Tree, Random Forest, XGBoost, and Neural Network, to predict the electrical energy output of a power plant based on temperature, ambient pressure, relative humidity, and exhaust vacuum.

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dionamuH/Eko

Rent estimator for Lagos apartments.

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dg-veiga/kaggle-house-pricing-regression

How to predict sales prices and practice feature engineering, RFs, and gradient boosting. Based on the competition hosted on Kaggle. Link=[https://www.kaggle.com/c/house-prices-advanced-regression-techniques]

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nikhilpatil44/rossmann-store-sales-prediction

Rossmann store sales prediction using XGBoost

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vargovema/real-estate-demand-ml

Predicting the Demand for Real Estate Listings in Austria

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Abhishekkohli/ML-Projects

HousingPriceRegression.py file contains project based on linear regression. The dataset comprises values of aspects related to residential places and price of a house. TitanicClassification.py file contains project based on binary classification. The dataset comprises of data related to passengers and binary value of whether they survived or not.

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elifsare/Medical-Insurance-Cost-Prediction

Medical Insurance Cost Prediction using XGBRegressor

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3rd-Son/bigmart_analysis

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sanchitmisra/Bike-sharing-demand-prediction

The objective of this research is to develop a prediction model using supervised regression machine learning that support the start-up for a stable supply of rental bikes.

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shruti-2412/Car-Price-Prediction

Predicting the current price of the car based on various features

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ved-et9/ipl_2023_score_predictor

🏏Predicting Ipl score on the model trained by Various ML algos 🔥,deployed the interface on hugging face for interacting with online users

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arka57/Ted-Talk-Views-Prediction

Building a predictive model to predict views of Ted Talks in YouTube from dataset of past events using Machine Learning models

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Sarvyi/Car101 Fork of adityapotdar23/Cars-101

Datahack 1.0

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siahyeelong/Predicting-HDB-Resale-Flat-Prices

This project was done as part of the Introduction to Data Science and AI module in NTU. In this project, my team explored on using 3 different models to predict the resale prices of a HDB flat given its features. As this was our first attempt at machine learning, the concepts used are pretty trivial

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Preetirai-tech/Bike-Sharing-Demand-Prediction

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.

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jsalarzai/House-Price-Prediction

House Price Prediction

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chesterchung1998/House-Price-Prediction

Machine learning prediction system for predicting prices of homes.

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chesterchung1998/BigMart-Sales-Prediction

Machine learning prediction system for predicting item sales of individual BigMart outlets.

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Amiir-zar/housing_price_regression_XGB

In this project, I delved into the fascinating world of real estate by employing the powerful XGBoost algorithm to develop a robust regression model

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AlaaMahmoud95/Concrete-Compressive-Strength

Regression Machine Learning Project

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shu-nya/Bike-Sharing-Demand-Prediction

Supervised ML (Regression) project on bike sharing demand prediction.

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hapl/predict-flight-delays

Midterm project Lighthouse Labs - Predicting flight delays project using machine learning algorithms in Python

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MatthewCSC/2021-Dengue-Fever-Prediction-Time-Series-

This repository contains the notebook used for the Spring 2021 Kaggle Dengue Fever Prediction Competition. Placement was in the top 10% with a MAE of 26. Our best approach involved XGBoost Regression on a reduced featureset selected with Recursive Feature Elimination in combination with correlation with the target (number of dengue cases).

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Katerinafomkina/House-Predicting-Advanced-Regression-Techniques

Predicting house price

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dfavenfre/Bike-Sharing-Demand-Prediction

Bike Rent Demand Prediction Model

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abhinav-bhardwaj/Walmart-Sales-Time-Series-Forecasting-Using-Machine-Learning

Time Series Forecasting of Walmart Sales Data using Deep Learning and Machine Learning

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scalable-ml-deep-learning/predicting-snow-conditions

Predicting Snow Conditions in Passo Tonale (Trento, Italy)

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roshancyriacmathew/Machine-learning-on-Big-Mart-Sales-Dataset

In this notebook, we will be performing machine learning on the Big mart sales dataset

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DavidNart90/AirBnB-Price-Prediction

This Project is a research on AirBnB house price prediction of 5 States in the USA. It Contains a Jupyter notebook which gives a detailed analytics of the house prices.

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RuochenT/predict-heart-disease

use XGBoost and Adaboost to predict heart disease and use SHAP to explain the potential factors behind the result.

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bogumilo/house-prices-xgboost

House prices dataset exploration and prediction. Workflow includes useful examples of Tensorflow pipelines including k-Nearest Neighbors imputer, Decision Tree Regression and XGBoost Regression

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itsayushthada/Frequency-Modelling

This is the project work related to the modelling of Frequency and associated parameters using Machine Learning.

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su050300/Predict_The_Price_Of_Books

Predict the price of books using XGBoost regressor,linear regression.

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KartaYu/PM2.5_Prediction_Time-Series-Regression

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sonu-gupta/Time-Series-Analysis-and-Anomaly-Detection

This repository contains code to perform EDA, outlier detection and forcasting on a multivariate time series.

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Keshav25-2002/Lanthanide-Series-Affinity-Prediction

This project uses machine learning algorithms to predict the binding affinity of a set of ligands to the Lanthanide series of elements. The binding affinity is an important property of a molecule and is defined as the strength of binding between the molecule and the target protein. The project aims to build a predictive model that can accurately

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AndreMenezesDS/rossmann_sales_predict

Sales Prediction for Rossmann Pharmaceutics database using Machine Learning regression modeling

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kunal-bhadra/Smart-Invoice-Manager

FullStack Webapp to help people in B2B Finance create and manage their invoices with ML

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rushandgg/XGBoost_Stock_Prediction

Predict stock price direction by using XGBoost

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Navneet2409/bike-sharing-demand-prediction

The goal of this project is to predict the demand for Seoul's Bike Sharing Program. A dataset (8760,14) containing historical usage patterns, such as temperature, time, and other relevant data is used to build a regression model.

Language: Jupyter Notebook - Size: 20.3 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

mendez-luisjose/Health-Insurance-Cost-Model

Linear Regression Health Insurance Cost Model with Different M.L. Algorithms

Language: Jupyter Notebook - Size: 391 KB - Last synced at: 4 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

shiv0112/ml_project_fifa

Created ML web app on European Soccer Database with around 97% accuracy to predict player overall rating.

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fa1zali/house_price_prediction_using_xgboost_regressor

A Machine Learning project using XGBoost Regressor for predicting house prices.

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Sineme01/House-Rate-Predictor

House Rate Predictor

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egedemirci/PoliticalTweet-and-Bot-Classifier-TurkishTwitterStudy

A machine learning study that detects political tweets and bot accounts on Twitter.

Language: Jupyter Notebook - Size: 12 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 2

kpsijil2/Cement-Manufacturing

Predicting cement strength

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kpsijil2/Big-Mart-Sales

Predicting Big mart sales

Language: Python - Size: 1.36 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

manashpratim/Big-Mart-Sales-Prediction

Predicting the sales of a store

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Suhas-2002/Bengaluru-House-Price-Predictor

A Web App used to Predict House Price in Bengaluru

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coolmunzi/end_to_end_ml-fitbit_calorie_counter

This is an End to end Machine Learning project based on Flask APIs covering model training and prediction pipelines for finding calorie from fitbit band's data.

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SuperMohit/ml-models

Fetches the data from MongoDB and creates xboost model for prediction

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arjunssat/Big_Mart_sales

Feature engineering synopsis

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Rumit95/Covid-Detection

The objective for this task is to demostrate the ability to build ML regression and clasification model and evalute its performance by prediting the required features

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dgovor/Housing-Price-Prediction-Python

Machine Learning model for price prediction using an ensemble of four different regression methods.

Language: Python - Size: 286 KB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

rsyamil/latent-space-xgboost

Latent space XGBoost for regression of latent variables representing high-dimensional multivariate timeseries in unconventional reservoirs.

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Kavya2099/Car-Price-Prediction

Car Price Prediction model created based on Regression algorithms

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805karansaini/AQI_Pre_v2

AQI Predictor V2 use multiple Supervised Machine Learning with Hyper tuning. ML algorithms used Linear Regressor, Lasso Regressor, Decision Tree Regressor, Random Forest Regressor, XGboost Regressor. The Model deployed on web and can predict AQI visit https://aqipredictor.up.railway.app/

Language: Python - Size: 141 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

cristianleoo/perfect-tuning

Kaggle Project. Predicting the rating of Spotify songs

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Jesus-Vazquez-A/Insurence

We solve a regression problem in which it consists of calculating the health insurance charge in the United States Where we will break down the project into 5 phases: Exploratory Analysis. Feature Engineering. Selection of the ideal model. Development of the final model. Creation of a web application in streamlit.

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Me-HDi/Historical-consumption-regression-for-electricity-supply-pricing

The goal of the challenge is to predict, based on the analysis of the correlation of a year of consumption and weather training data, the electricity consumption of two given sites for a test year.

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artisan1218/Recommendation-System

Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity

Language: Python - Size: 63 MB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 4 - Forks: 1

posi-olomo/House-Prices---Advanced-Regression-Techniques

I participated in the "House Prices" Competition where I trained a machine learning algorithm to help users to easily predict the price of their house based on information regarding the size and location of the house

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harshit1531/Mercedes-Benz-Greener-Manufacturing

Reduce the time that cars spend on the test bench. Work with a dataset representing different permutations of features in a Mercedes-Benz car to predict the time it takes to pass testing. Optimal algorithms will contribute to faster testing, resulting in lower carbon dioxide emissions without reducing Mercedes-Benz’s standards.

Language: Jupyter Notebook - Size: 857 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

iamsj2022/Job-a-ThonNOVAV

Analytic Vidhya's Problem Statement to Predict or Forecast the Future Energy Demand For Next Three Years.

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sam-marhaendra/carprice-predictor

This is a web-based application that can give a recommendation about estimated car price by inferencing its specifications.

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fa1zali/medical_insurance_cost_prediction

A Machine Learning model using Linear Regression & XGBoost Regressor for predicting the Medical Insurance cost for an individual

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RanjeetKumbhar01/WW2-Temperature-Regression

Weather Conditions in WW2 with Linear Reg ,Lasso Reg, Decision Tree Reg, Random Forest Reg, XGBoost Reg, Bagging Reg, Neural Network

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somjit101/Netflix-Movie-Recommendation

A case study of the Netflix Prize solution where, given anonymous data of users and the ratings given to movies, the objective to provide recommendations to users for movies which they would like, based on their past activity and taste.

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nidragedd/udadsnd-p4-airbnb_inside

Udacity DataScience nanodegree 4th project: pick a dataset, explore it and write a blog post

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kyaiooiayk/XGBoost-notes

Notes, tutorials, code snippets and templates focused on XGBoost for Machine Learning

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kaledhoshme123/A-proposed-model-that-can-predict-the-assessment-of-both-Syntax-Cohesion-Vocabulary-Phraseology-

The proposed model is able to predict the evaluation of both grammatical coherence, vocabulary and grammatical conventions, so that the evaluation can give each of those criteria a value between 1 and 5, I did not treat the system as a classification process, but rather it was treated as a REGRESSION issue. It includes several steps through which a few errors were reached, all ranging between 0.25 for each criterion. The values ​​of the weights that were reached can also be used to deal with the issue as a classification process (but it was not dealt with as well in this proposed methodology).

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Bayunova28/Moderna_Vaccine_Stock

This repository contains about group final exam of machine learning course at my college

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