{"repo":"ashishpatel26/Amazing-Feature-Engineering","free":true,"listed":false,"github":"https://github.com/ashishpatel26/Amazing-Feature-Engineering","clone":"git clone https://github.com/ashishpatel26/Amazing-Feature-Engineering.git","description":"Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.","language":"Jupyter Notebook","stars":807,"topics":["feature-engineering","machine-learning","deep-learning","scikit-learn","data-mining","data-science","data-scientists","feature-scaling","feature-extraction","feature-selection"],"license":null,"category":"machine-learning","readme_excerpt":"Feature Engineering & Feature Selection A comprehensive guide [[pdf]](https://github.com/ashishpatel26/Amazing-Feature-Engineering/blob/master/A%20Short%20Guide%20for%20Feature%20Engineering%20and%20Feature%20Selection.pdf) [[markdown]](https://github.com/ashishpatel26/Amazing-Feature-Engineering/blob/master/A%20Short%20Guide%20for%20Feature%20Engineering%20and%20Feature%20Selection.md) for Feature Engineering and Feature Selection , with implementations and examples in Python. Motivation Feature Engineering & Selection is the most essential part of building a useable machine learning project, even though hundreds of cutting-edge machine learning algorithms coming in these days like deep learning and transfer learning. Indeed, like what Prof Domingos, the author of 'The Master Algorithm' says: “At the end of the day, some machine learning projects succeed and some fail. What makes the difference? Easily the most important factor is the features used.” — Prof. Pedro Domingos Data and feature has the most impact on a ML project and sets the limit of how well we can do, while models and algorithms are just approaching that limit. However, few materials could be found that systematically introduce the art of feature engineering, and even fewer could explain the rationale behind. This repo is my personal notes from learning ML and serves as a reference for Feature Engineering & Selection. Download Download the PDF here: - PDF Download Same, but in markdown: - Mark Down Download PD","default_branch":null,"files":null,"tree":[],"storefront":"/r/ashishpatel26","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ashishpatel26/Amazing-Feature-Engineering/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}