decision-tree-regression
There are 333 repositories under decision-tree-regression topic.
srafay/Machine_Learning_A-Z
Learning to create Machine Learning Algorithms
Suji04/ML_from_Scratch
Implementation of basic ML algorithms from scratch in python...
rahuldkjain/Crop_Prediction
ApnaAnaaj aims to solve crop value prediction problem in an efficient way to ensure the guaranteed benefits to the poor farmers. The team decided to use Machine Learning techniques on various data to came out with better solution. This solution uses Decision Tree Regression technique to predict the crop value using the data trained from authentic datasets of Annual Rainfall, WPI Index for about the previous 10 years. This implementation proved to be promising with 93-95% accuracy.
eaglewarrior/Machine-learning
This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates
Anindya-Das02/Comparison-of-ML-models-for-predicting-AQI
In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).
Dalageo/ML-GasSensorDrift
Drift Detection in Gas Sensor Array at Different Concentration Levels ☢️
emirhanai/Machine-Learning-Software-that-predicts-planets-based-on-their-distance-from-the-sun-number-of-sate
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
leihao1/Comparison-of-Machine-Learning-Prediction-Models
Compared different classification and regreesion models performance in scikit-learn by applying them on 20 datasets from UCL website.
bissessk/Regression-Analysis-of-COVID-19
The objective of this project is to study the COVID-19 outbreak using basic statistical techniques and make short term predictions using ML regression methods.
omarmhaimdat/xgboost_student_performance
Introduction to XGBoost with an Implementation in an iOS Application
smartinternz02/SI-GuidedProject-4884-1627462177
Natural Gas Price Prediction System Using IBM Watson services
Chandrakant817/Calories-Burned-Prediction
Calories-Burned-Prediction Using Machine Learning. (Regression Use Case)
mukulsinghal001/USA-Housing-Price-Prediction
In this project I have implemented 14 different types of regression algorithms including Linear Regression, KNN Regressor, Decision Tree Regressor, RandomForest Regressor, XGBoost, CatBoost., LightGBM, etc. Along with it I have also performed Hyper Paramter Optimization & Cross Validation.
omarmhaimdat/WeatherPrediction
Weather Prediction iOS Application Using Flask API and AI
saichandrareddy1/Machine_Learning_basics
This is repository about the MachineLaering Basics including all the Machine learning Algorithms
vamc-stash/Decision-Tree
Implements Decision tree classification and regression algorithm from scratch in Python.
XavierCarrera/Tutorial-Machine-Learning-Arboles
Los árboles de decisión son uno de los algoritmos clásicos de machine learning ya que nos ayudan a visualizar las predicciones hechas por nuestro modelo. En este tutorial vemos su uso para regresiones lineares y clasificación, así como herramientas de ensamble como bagging y boosting.
coderjolly/player-market-value-prediction
There is an intense transfer speculation that surrounds all major player transfers today. An important part of negotiations is predicting the fair market price for a player. Therefore, we are predicting this Market Value of a player using the data provided in csv format.
georgemuriithi/shale-gas-wells
The Korea National Oil Corporation was interested in purchasing shale gas wells from the United States and wanted to predict their production to select wells that maximize profit.
Joycechidi/MachineLearning
All my Machine Learning Projects from A to Z in (Python & R)
mahesh147/Decision-Tree-Regression
Implementation of a 1D Decision Tree Regression model in python.
pavankalyan1997/Machine-Learning-Using-Scikit-learn-and-other-libraries
Machine Learning algorithms implementation using Python
agrawal-priyank/Machine-Learning-Models-For-Insurance-Loan-Applicants
Academic project for Advances in Data Science and Architecture course
aws-samples/sagemaker-weather-prediction
This repository contains the files and instructions on using Amazon SageMaker to build linear regression, polynomial regression etc to predict the temperature
joaqrus/EnergyDissagregation
Segmentación Energía usando dataset REDD y varios algoritmos incluidos Neural Network
mtasgetiren/Car-Prices-Prediction
Prediction of car prices using data from sahibinden.com
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.
suriya-1403/Natural-Gas-Price-Prediction-System
Natural Gas Price Prediction System Using IBM Watson services
tanmay-d-shah/Crop_Price_Prediction_Dashboard
A ReactJS based dashboard predicting crop prices using Decision Tree Regression Algorithm.
Akash1070/BigMart-Sales-Prediction-
Building BigMart Sales Prediction
AmirMotefaker/Predicting-Sales-Ecommerce
Sales forecast for managing cash flow in the future.
asaldelkhosh/Music-Recommender
Implementing a music recommender with decision tree.
Mohshaikh23/Retail-Price-Optimization
Retail Price Optimization using Python
PriyankaSett/predicting_instagram_likes
The aim of this work is to predict number of instagram likes. The text vectorization is done using TF-IDF Vectorizer.
samagra44/Zomato-Delivery-Time-Prediction
The Zomato Delivery Time Prediction Application is a machine learning-driven Flask web application designed to predict the estimated delivery time for food orders placed on the Zomato platform.
shaadclt/House-Price-Prediction-DecisionTreeRegressor
This project involves the prediction of house prices in Bengaluru city using Decision Tree Regression in Jupyter Notebook. Through this analysis, we aim to build a regression model that accurately predicts house prices based on the given input features.