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Feature Selection for Machine Learning Udemy

@machinelearnbot

Learn how to select features and build simpler, faster and more reliable machine learning models. This is the most comprehensive, yet easy to follow, course for feature selection available online. Throughout this course you will learn a variety of techniques used worldwide for variable selection, gathered from data competition websites and white papers, blogs and forums, and from the instructor's experience as a Data Scientist. You will have at your fingertips, altogether in one place, multiple methods that you can apply to select features from your data set. The course starts describing simple and fast methods to quickly screen the data set and remove redundant and irrelevant features.



Feature Selection for Machine Learning

#artificialintelligence

Welcome to Feature Selection for Machine Learning, the most comprehensive course on feature selection available online. In this course, you will learn how to select the variables in your data set and build simpler, faster, more reliable and more interpretable machine learning models. Who is this course for? You've given your first steps into data science, you know the most commonly used machine learning models, you probably built a few linear regression or decision tree based models. You are familiar with data pre-processing techniques like removing missing data, transforming variables, encoding categorical variables.


Feature Selection for Machine Learning

#artificialintelligence

Welcome to Feature Selection for Machine Learning, the most comprehensive course on feature selection available online. In this course, you will learn how to select the variables in your data set and build simpler, faster, more reliable and more interpretable machine learning models. Who is this course for? You've given your first steps into data science, you know the most commonly used machine learning models, you probably built a few linear regression or decision tree based models. You are familiar with data pre-processing techniques like removing missing data, transforming variables, encoding categorical variables.


Feature Selection for Machine Learning

#artificialintelligence

Having irrelevant features in your data can decrease the accuracy of the models and make your model learn based on irrelevant features. This is the most comprehensive, yet easy to follow, course for feature selection available online. Throughout this course you will learn a variety of techniques used worldwide for variable selection, gathered from data competition websites and white papers, blogs and forums, and from the instructor's experience as a Data Scientist. You will have at your fingertips, altogether in one place, multiple methods that you can apply to select features from your data set.