This repository contains the code to predict house price using Linear Regression Method

Overview

House-Price-Prediction-Using-Linear-Regression

GitHub last commit

The dataset I used for this personal project is from Kaggle uploaded by aariyan panchal.

Link of Dataset : https://www.kaggle.com/aariyan101/usa-housingcsv.

File Python/main.py contains the code that used for doing the prediction of House Price using Linear Regression Method.

File Dataset/USA_Housing.csv is the dataset that I used for this research.

File Model/housePredictionModel.pickle is the result of model that I trained in Pickle Format with highest Accuracy.

File Output/.. is the output of this research. The data is plotted using Matplotlib.

Linear Regression

  Linear regression analysis is used to predict the value of a variable based on the value of another variable. 
  The variable you want to predict is called the dependent variable. 
  The variable you are using to predict the other variables value is called the independent variable. 
  Linear Regression is one of the method Supervised Learning.
  [[IBM](https://www.ibm.com/topics/linear-regression)].

Supervised Learning

  Supervised learning is a machine learning approach that’s defined by its use of labeled datasets. 
  These datasets are designed to train or “supervise” algorithms into classifying data or predicting outcomes accurately. 
  Using labeled inputs and outputs, the model can measure its accuracy and learn over time.
  [[IBM](https://www.ibm.com/cloud/blog/supervised-vs-unsupervised-learning)].

Picture 1.1 Result of Linear Regression (Avg. Area Income, Price)

Picture 1.2 Result of Linear Regression (Area Population, Price)

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

Sebastian Raschka 4.2k Dec 29, 2022
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.

Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led

Brett Vogelsang 2 Jan 18, 2022
Open MLOps - A Production-focused Open-Source Machine Learning Framework

Open MLOps - A Production-focused Open-Source Machine Learning Framework Open MLOps is a set of open-source tools carefully chosen to ease user experi

Data Revenue 590 Dec 28, 2022
CD) in machine learning projectsImplementing continuous integration & delivery (CI/CD) in machine learning projects

CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance

Iterative 19 Oct 03, 2022
Combines Bayesian analyses from many datasets.

PosteriorStacker Combines Bayesian analyses from many datasets. Introduction Method Tutorial Output plot and files Introduction Fitting a model to a d

Johannes Buchner 19 Feb 13, 2022
Mortality risk prediction for COVID-19 patients using XGBoost models

Mortality risk prediction for COVID-19 patients using XGBoost models Using demographic and lab test data received from the HM Hospitales in Spain, I b

1 Jan 19, 2022
A scikit-learn based module for multi-label et. al. classification

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

802 Jan 01, 2023
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

PyCaret 6.7k Jan 08, 2023
The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it inside a loop of Design, Model Development and Operations.

MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid

Maykon Schots 25 Nov 27, 2022
Automatically create Faiss knn indices with the most optimal similarity search parameters.

It selects the best indexing parameters to achieve the highest recalls given memory and query speed constraints.

Criteo 419 Jan 01, 2023
A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize

⚡ funk-svd funk-svd is a Python 3 library implementing a fast version of the famous SVD algorithm popularized by Simon Funk during the Neflix Prize co

Geoffrey Bolmier 171 Dec 19, 2022
Probabilistic time series modeling in Python

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

Amazon Web Services - Labs 3.3k Jan 03, 2023
Stats, linear algebra and einops for xarray

xarray-einstats Stats, linear algebra and einops for xarray ⚠️ Caution: This project is still in a very early development stage Installation To instal

ArviZ 30 Dec 28, 2022
🌊 River is a Python library for online machine learning.

River is a Python library for online machine learning. It is the result of a merger between creme and scikit-multiflow. River's ambition is to be the go-to library for doing machine learning on strea

OnlineML 4k Jan 03, 2023
A simple machine learning python sign language detection project.

SST Coursework 2022 About the app A python application that utilises the tensorflow object detection algorithm to achieve automatic detection of ameri

Xavier Koh 2 Jun 30, 2022
This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you ask it.

Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you

Hazim Arafa 6 Dec 04, 2022
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Microsoft 241 Dec 26, 2022
BASTA: The BAyesian STellar Algorithm

BASTA: BAyesian STellar Algorithm Current stable version: v1.0 Important note: BASTA is developed for Python 3.8, but Python 3.7 should work as well.

BASTA team 16 Nov 15, 2022
A comprehensive repository containing 30+ notebooks on learning machine learning!

A comprehensive repository containing 30+ notebooks on learning machine learning!

Jean de Dieu Nyandwi 3.8k Jan 09, 2023
Pyomo is an object-oriented algebraic modeling language in Python for structured optimization problems.

Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models. Pyomo can be used to define symbolic p

Pyomo 1.4k Dec 28, 2022