How to predict House Prices in Ames, Iowa | Kaggle Competition in Data Science & Machine Learning

Описание: In this video, I go over the dataset provided in the "House Prices" competition on Kaggle (https://www.kaggle.com/c/house-prices...) and use Python (in particular, numpy, pandas, and sklearn) to train machine learning models that predict the prices of house in the city of Ames, Iowa.

The case study emphasizes the importance of data cleaning and feature generation, referred to as the "dirty work" by data scientists, in getting better results.

The shown code and data are available for free under the MIT open source license on GitHub: https://github.com/webartifex/ames-ho...

PYTHON BOOK & LECTURES
For more background on Python & programming, check my free book on GitHub: https://github.com/webartifex/intro-t...
A free full-semester video course covering the book is available here:    • Intro to Python & Programming (Spring 2020...  

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The videos focus on coding courses and tutorials aimed at managers and students of business administration, enabling them to make better decisions with analyses done in code.

INSTRUCTOR
Alexander Hess, PhD Student
WHU - Otto Beisheim School of Management, Vallendar, Germany

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