boston-housing-price-prediction
There are 2 repositories under boston-housing-price-prediction topic.
ASHOKKUMAR-K / Machine-Learning-Projects
Machine Learning - End to End Data Science Projects
Language:Jupyter Notebook 117rahulravindran0108 / Boston-House-Price-Prediction
This repository contains files for Udacity's Machine Learning Nanodegree Project: Boston House Price Prediction
Language:Python 48- keras_boston_housing_price
rodrigobressan / keras_boston_housing_price
Keras 101: A simple Neural Network for House Pricing regression
Language:Jupyter Notebook 15 - Language:Jupyter Notebook 11
qin-yu / julia-regression-boston-housing
2018 [Julia v1.0] machine learning (linear regression & kernel-ridge regression) examples on the Boston housing dataset
Language:Julia 11shushrutsharma / data-science-machine-learning-toolkit
All the essential resources and template code needed to understand major data science and machine learning libraries like Numpy, Pandas, Matplotlib and Scikit Learn with few small projects to demonstrate their practical application.
Language:Jupyter Notebook 7aahouzi / Optimization-for-Machine-Learning
Implementation of 11 variants of Gradient Descent algorithm from scratch, applied to the Boston Housing Dataset.
Language:Jupyter Notebook 6JangirSumit / BostonHousePricePrediction
Predicting Boston House Prices
Language:Jupyter Notebook 5matin-ghorbani / perceptron
Implement a perceptron from scratch
Language:Jupyter Notebook 5KeeratSachdeva / GRADIENT-DESCENT-BOSTON
An Implementation of the Gradient Descent Algorithm on the 🏡Boston Housing DataSet🏡.
Language:HTML 4lmego / boston_housing
Boston Housing Prediction - 2nd project for Udacity's Machine Learning Nanodegree
Language:HTML 4- Bostone-housing-price-prediction
ahmadali-jamali / Bostone-housing-price-prediction
Dataset Boston Housing Price prediction
Language:Python 3 - Language:Jupyter Notebook 3
mayur29 / Udacity_Machine_Learning_Projects
These are all the assignments from Udacity Nanodegree Machine Learning course
Language:Jupyter Notebook 3sabeelahmad / Gradient-Descent
Gradient Descent for N features using two datasets: Boston House data, Power Plant Data
Language:Jupyter Notebook 3- Language:Jupyter Notebook 3
sujitmandal / Machine-Learning
Linear Regression , Cross Validation, k-mean clustering , Watershed , Gradients and Edge Detection , threshold , Correlation , Neural Network, Conventional Neural Network , Pneumonia Classification, Social Distancing, Rainfall Prediction, Boston Housing Price Prediction.
machine-learningneural-networksupervised-learninglinear-regressionclassificationconvolutional-neural-networkscomputer-visionk-means-clusteringwatershedgradientedge-detectionrainfall-predictionboston-housing-price-predictioncorrelationcross-validationhandwritten-digit-recognitionthresholdpneumonia-classificationregressionLanguage:Python 3DavidCico / Boston-House-Prices-With-Regression-Machine-Learning-and-Keras-Deep-Learning
In this repository, a regression analysis is conducted using different machine learning and deep learning models. The study is led in order to choose the most suitable model by looking at different characteristics (models tuning, features scaling, etc).
Language:Jupyter Notebook 2Kunal1198 / House-Price-Prediction-ML
The objective is to build a regression model to predict the price of houses.
Language:Jupyter Notebook 2msampathkumar / machine-learning
Content for Udacity's Machine Learning curriculum
Language:Jupyter Notebook 2- Predicting-Boston-Housing-Prices
sushantdhumak / Predicting-Boston-Housing-Prices
Machine Learning Nano-degree Project : To assist a real estate agent and his/her client with finding the best selling price for their home
pythonscikitlearn-machine-learningdecision-tree-regressionmodel-complexitymodel-selectionmodel-validationmatplotlib-pyplotregression-modelsboston-housing-price-predictionboston-housing-pricesboston-housing-datasetgridsearchcvcross-validationlearning-curvecomplexity-curvecomplexity-analysismachine-learninghousing-pricesbostonscikit-learnLanguage:Jupyter Notebook 2 thenomaniqbal / boston-housing-price-prediction
This project is about predicting house price of Boston city using supervised machine learning algorithms. In this we used three models Multiple Linear Regression, Decision Tree and Random Forest and finally choose the best one. Furthermore, we briefly introduced Regression, the data set, analyzed and visualized the dataset.
Language:Jupyter Notebook 2UtkarshMishra04 / Machine-Learning-Projects
The repository contains various Machine Learning based solutions for data analysis, regression and clustering problems
Language:Jupyter Notebook 2valerio / boston-housing
A project built as part of the udacity machine learning ND
Language:HTML 2VetlaPavanKalyan / Boston-Housing-Price-Prediction
Linear Regression model trained on Boston Housing Dataset
Language:Jupyter Notebook 2vishalv91 / capstoneproject-realestate
Data: Boston Housing Dataset (HousingData.csv) Programming language(s): R Tool(s): RStudio Business problem: To understand the drivers behind the value of houses in Boston and provide data-driven recommendation to the client on how they can increase the value of housing.The Boston housing dataset consisted of 506 observations and 14 variables. Project challenge(s): MEDV (Median value of homes in Boston) was identified as the dependent variable. While the rest, were the independent variables. The goal was to find out which among the independent variables were statistically significant in driving the house prices (MEDV). The dataset consisted of missing values and outliers. Some of the variables had a skewed distribution. There was multicollinearity among few independent variables. Our Approach: Prior to model building, we tidied up our dataset by eliminating the rows that contained missing values. Replacing the missing values with median and mean of those variables were also done. Considering the three approaches, median imputation(replacing missing values with mean) was found to be the best approach. As the dependent variable "MEDV" (median value of houses) was continuous(numerical) in nature, we implemented the Multiple linear regression to build our model. Additional models were built from Decision trees and Random forest. On further investigation, we discovered that the dependent variable had a skewed distribution. By log transformation of this variable, we were able to get a normal distribution. Post transformation, we found out that the model built from Multiple linear regression with log transformed MEDV was the best in terms of MSE (Mean squared error) value and Adjusted R^2. All the assumptions of linear regression were met.
Language:R 2y-martinez / machine-learning-microservices
Project #4 from the Cloud DevOps Engineer Nanodegree Program - Udacity
Language:Shell 2aps19 / B-Spline-Regression
Regression by diviging data into bins and fitting different degree of polynomials on each bin.
Language:Jupyter Notebook 1- Language:Jupyter Notebook 1
DHwass / XGBoost-on-Home-Data-KAGGLE
In this project, XGBoost is applied to forecast real estate prices using the Boston Housing Dataset. The primary aim is to create an effective predictive model, assess its accuracy through metrics like Mean Absolute Error (MAE), and refine its performance by tuning hyperparameters with HYPEROPT.
Language:Jupyter Notebook 1EN10 / BostonHousing
Boston Housing Dataset Example
Language:Jupyter Notebook 1geekquad / Boston-Housing
Evaluating the performance and predictive power of a model. Cross questioned several concepts of ML for better understanding.
Language:Jupyter Notebook 1michstg / HousePricePrediction-selectfeature
Regression-PrediksiHargaRumahBoston-kaggle-ensamblemodel-supervisedlearning
Language:Jupyter Notebook 1radadiyamohit81 / Boston_Housing_Price_Prediction
The main motive of this project is Price Prediction on the Boston Housing dataset. and here mainly focused on the Implementation using Linear Regression Model.
Language:Jupyter Notebook 1Raptor2804 / Predict_Boston_House_Prices_Using_Python_and_Linear_Regression
The Linear regression model is implemented on Boston house prices dataset.
Language:Jupyter Notebook 1ZarahShibli / Boston-Housing-Price-Predict
This project to predict Boston housing price using linear regression
Language:Jupyter Notebook 1
