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Title: GitHub - CallmeHenry/AppleStore_Machine-Learning: Applied machine learning techniques to the Apple App store dataset to find the most impactful variables involved that determines an app's price. Applied regression techniques and feature subset selection to find variable importance (price prediction via feature engineering). Written in Python 3 and markdown via Jupyter.

Open Graph Title: GitHub - CallmeHenry/AppleStore_Machine-Learning: Applied machine learning techniques to the Apple App store dataset to find the most impactful variables involved that determines an app's price. Applied regression techniques and feature subset selection to find variable importance (price prediction via feature engineering). Written in Python 3 and markdown via Jupyter.

X Title: GitHub - CallmeHenry/AppleStore_Machine-Learning: Applied machine learning techniques to the Apple App store dataset to find the most impactful variables involved that determines an app's price. Applied regression techniques and feature subset selection to find variable importance (price prediction via feature engineering). Written in Python 3 and markdown via Jupyter.

Description: Applied machine learning techniques to the Apple App store dataset to find the most impactful variables involved that determines an app's price. Applied regression techniques and feature subset selection to find variable importance (price prediction via feature engineering). Written in Python 3 and markdown via Jupyter. - CallmeHenry/AppleStore_Machine-Learning

Open Graph Description: Applied machine learning techniques to the Apple App store dataset to find the most impactful variables involved that determines an app's price. Applied regression techniques and feature subset...

X Description: Applied machine learning techniques to the Apple App store dataset to find the most impactful variables involved that determines an app's price. Applied regression techniques and feature su...

Opengraph URL: https://github.com/CallmeHenry/AppleStore_Machine-Learning

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