Udemy - Feature Engineering for Machine Learning (updated 10-2019)

[ FreeCourseWeb.com ] Feature Engineering for Machine Learning (updated 10/2019)



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Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz

Language: English | VTT | Size: 3.76 GB | Duration: 9.5 hours

What you'll learn

Learn multiple techniques for missing data imputation

Transform categorical variables into numbers while capturing meaningful information

Learn how to deal with infrequent, rare and unseen categories

Transform skewed variables into Gaussian

Convert numerical variables into discrete

Remove outliers from your variables

Extract meaningful features from dates and time variables

Learn techniques used in organisations worldwide and in data competitions

Increase your repertoire of techniques to preprocess data and build more powerful machine learning models



Requirements

A Python installation

Jupyter notebook installation

Python coding skills

Some experience with Numpy and Pandas

Familiarity with Machine Learning algorithms

Familiarity with Scikit-Learn

Description

NEW! Updated in November 2019 for the latest software versions, including use of new tools and open-source packages, and additional feature engineering techniques.



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Welcome to Feature Engineering for Machine Learning, the most comprehensive course on feature engineering available online. In this course, you will learn how to engineer features and build more powerful machine learning models.



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