Regression Analysis into the Boston Housing in-demand pricing in 1978

Exploratory Data Analysis of Boston Housing Dataset Using R

Boston Housing Price prediction using regressions

Visualizing rent affordability in East Boston

This repository contains code and associated files for deploying ML models using AWS SageMaker. This repository consists of a number of tutorial notebooks for various coding exercises, mini-projects, and project files that will be used to supplement the lessons of the Nanodegree.

This project uses Mini-learn on Boston's housing data-set. Mini-learn is a miniature version of tensor-flow which I made to play around with neural nets. See https://github.com/Satyaki0924/minilearn for more information.

Projects of Udacity's Machine Learning Specialization Nanodegree program.

Code and associated files created or filled in, used in my learning during the Machine Learning Engineer Udacity Nanodegree Program

Predicting housing prices using machine learning and the widely available Boston Housing dataset.

This code file predicts the House prices (MEDV) based on given features.

Projects completed in the Urban Informatics masters degree program at Northeastern University - All projects completed in R

Implementing linear regression on Boston Housing dataset using scikit-learn

Repository for Assignment 1 for CS 725

Predicting Boston house prices with Machine Learning.

Udacity MLND P1: Predicting Boston Housing prices

This repository showcases projects that I have done as a partial fulfillment for Udacity's Machine-Learning Nano Degree program. The projects involve Supervised Machine Learning, Unsupervised Machine Learning , Reinforcement Learning as tools to solve the data driven problems coming from different real life situations.

MA Housing Assistance APP

Predicting house prices of the "Boston Housing" dataset.

This repo contains projects developed in Machine Learning Foundation Nanodegree.