Acerca de este Curso
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Subtítulos: Inglés (English)

Qué aprenderás

  • Check

    Describe machine learning methods such as regression or classification trees

  • Check

    Explain the complete process of building prediction functions

  • Check

    Understand concepts such as training and tests sets, overfitting, and error rates

  • Check

    Use the basic components of building and applying prediction functions

Habilidades que obtendrás

Random ForestMachine Learning (ML) AlgorithmsMachine LearningR Programming

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Aprox. 14 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
2 horas para completar

Week 1: Prediction, Errors, and Cross Validation

This week will cover prediction, relative importance of steps, errors, and cross validation.

...
9 videos (Total 73 minutos), 3 readings, 1 quiz
9 videos
What is prediction?8m
Relative importance of steps9m
In and out of sample errors6m
Prediction study design9m
Types of errors10m
Receiver Operating Characteristic5m
Cross validation8m
What data should you use?6m
3 lecturas
Welcome to Practical Machine Learning10m
Syllabus10m
Pre-Course Survey10m
1 ejercicio de práctica
Quiz 110m
Semana
2
2 horas para completar

Week 2: The Caret Package

This week will introduce the caret package, tools for creating features and preprocessing.

...
9 videos (Total 96 minutos), 1 quiz
9 videos
Data slicing5m
Training options7m
Plotting predictors10m
Basic preprocessing10m
Covariate creation17m
Preprocessing with principal components analysis14m
Predicting with Regression12m
Predicting with Regression Multiple Covariates11m
1 ejercicio de práctica
Quiz 210m
Semana
3
1 hora para completar

Week 3: Predicting with trees, Random Forests, & Model Based Predictions

This week we introduce a number of machine learning algorithms you can use to complete your course project.

...
5 videos (Total 48 minutos), 1 quiz
5 videos
Bagging9m
Random Forests6m
Boosting7m
Model Based Prediction11m
1 ejercicio de práctica
Quiz 310m
Semana
4
4 horas para completar

Week 4: Regularized Regression and Combining Predictors

This week, we will cover regularized regression and combining predictors.

...
4 videos (Total 33 minutos), 2 readings, 3 quizzes
4 videos
Combining predictors7m
Forecasting7m
Unsupervised Prediction4m
2 lecturas
Course Project Instructions (READ FIRST)10m
Post-Course Survey10m
2 ejercicios de práctica
Quiz 410m
Course Project Prediction Quiz40m
4.5
465 revisionesChevron Right

42%

comenzó una nueva carrera después de completar estos cursos

41%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

15%

consiguió un aumento de sueldo o ascenso

Principales revisiones sobre Practical Machine Learning

por ADMar 1st 2017

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

por ASAug 31st 2017

Highly recommend this course. It makes you read a lot, do lot's of practical exercises. The final project is a must do. After finishing this course you can start playing with kaggle data sets.

Instructores

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Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

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Preguntas Frecuentes

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