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Machine Learning with caret in R

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

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4 Horas24 Videos88 Ejercicios
56.558 AprendicesTrophyDeclaración de cumplimiento

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Descripción del curso

Machine learning is the study and application of algorithms that learn from and make predictions on data. From search results to self-driving cars, it has manifested itself in all areas of our lives and is one of the most exciting and fast growing fields of research in the world of data science. This course teaches the big ideas in machine learning: how to build and evaluate predictive models, how to tune them for optimal performance, how to preprocess data for better results, and much more. The popular caret R package, which provides a consistent interface to all of R's most powerful machine learning facilities, is used throughout the course.
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  1. 1

    Regression Models: Fitting and Evaluating Their Performance

    Gratuito

    In the first chapter of this course, you'll fit regression models with train() and evaluate their out-of-sample performance using cross-validation and root-mean-square error (RMSE).

    Reproducir Capítulo Ahora
    Welcome to the course
    50 xp
    In-sample RMSE for linear regression
    50 xp
    In-sample RMSE for linear regression on diamonds
    100 xp
    Out-of-sample error measures
    50 xp
    Out-of-sample RMSE for linear regression
    50 xp
    Randomly order the data frame
    100 xp
    Try an 80/20 split
    100 xp
    Predict on test set
    100 xp
    Calculate test set RMSE by hand
    100 xp
    Comparing out-of-sample RMSE to in-sample RMSE
    50 xp
    Cross-validation
    50 xp
    Advantage of cross-validation
    50 xp
    10-fold cross-validation
    100 xp
    5-fold cross-validation
    100 xp
    5 x 5-fold cross-validation
    100 xp
    Making predictions on new data
    100 xp

En las siguientes pistas

Fundamentos del machine learning en RCientífico de Machine Learning con R

Colaboradores

Collaborator's avatar
Nick Carchedi
Collaborator's avatar
Tom Jeon
Zachary Deane-Mayer HeadshotZachary Deane-Mayer

VP, Data Science at DataRobot

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