Kaggle House Prices: Advanced Regression Techniques.Public Leaderboard Score 0.12076.
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Updated
Feb 14, 2017 - Jupyter Notebook
Kaggle House Prices: Advanced Regression Techniques.Public Leaderboard Score 0.12076.
[Done] Master version: developed the stacked regression (score 0.11, top 5%) based on (xgboost, sklearn). Branch v1.0: developed linear regression (score 0.45) based on Tensorflow
My analysis of Kaggle Contest problems
All of mine ML projects
This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.
This project consists in competing in the following Kaggle competition: https://www.kaggle.com/c/house-prices-advanced-regression-techniques
Kaggle project using regression models to predict housing price.
Deep Learning using Tensorflow for the "House Prices: Advanced Regression Techniques" Kaggle competition.
Kaggle Competition for Regression
Repository for source code of Kaggle competition: House Prices: Advanced Regression Techniques
All my Kaggle Notebooks that I've published
Machine Learning
This gives detailed python code for most common datasets for beginners. This repository has used examples which display the different libraries of python including numpy, pandas, seaborn, sklearn and many others.
Kaggle House Prices Problem
Predict sales prices and practice feature engineering, RFs, and gradient boosting
This repo. contains my various approaches towards the problem : https://www.kaggle.com/c/house-prices-advanced-regression-techniques
My Data Mining Training Repository
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