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)
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Updated
Apr 9, 2019 - Python
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)
An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.
Building Toronto Housing dataset from scratch to predict real estate prices
Project work and Assignments for Machine learning specialization course on Coursera by University of washington
Training and Deployment of model which predicts house prices around Boston using Neural Networks (keras)
Predicting house prices in Boston with python/scikit-learn
A collection of Data Science and Data Analysis projects to demonstrate my skill set in Python, Pandas, R, and machine learning
Advanced Regression Techniques to predict housing prices.
Machine Learning Algorithms using GraphLab
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.
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