Predicting house prices in Boston with python/scikit-learn
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Updated
Oct 1, 2016 - HTML
Predicting house prices in Boston with python/scikit-learn
Advanced Regression Techniques to predict housing prices.
Project work and Assignments for Machine learning specialization course on Coursera by University of washington
Machine Learning Algorithms using GraphLab
Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
Training and Deployment of model which predicts house prices around Boston using Neural Networks (keras)
Building Toronto Housing dataset from scratch to predict real estate prices
This repo contains assignments for Coursera course (ML Foundations: A Case Study Approach
Determining the best model to predict house prices in Kings County, Seattle.
My solution to the House Prices Challenge on Kaggle.
An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.
A collection of Data Science and Data Analysis projects to demonstrate my skill set in Python, Pandas, R, and machine learning
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