Cientista de aprendizado de máquina com R

Domine as habilidades essenciais para conseguir um emprego como cientista de aprendizado de máquina! Você aumentará seu conjunto de habilidades de programação em R com a caixa de ferramentas para realizar aprendizado supervisionado e não supervisionado. Você aprenderá a processar dados para modelagem, treinar seus modelos, visualizar seus modelos e avaliar seu desempenho, além de ajustar seus parâmetros para obter melhor desempenho. No processo, você terá uma introdução à estatística bayesiana, ao processamento de linguagem natural e ao Spark.

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Supervised Learning in R: Classification

In this course you will learn the basics of machine learning for classification.

4 hours

Supervised Learning in R: Regression

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

4 hours

Feature Engineering in R

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

4 hours

Unsupervised Learning in R

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

4 hours

Machine Learning in the Tidyverse

Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.

5 hours

Intermediate Regression in R

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hours

Cluster Analysis in R

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

4 hours

Machine Learning with caret in R

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

4 hours

Modeling with tidymodels in R

Learn to streamline your machine learning workflows with tidymodels.

4 hours

Machine Learning with Tree-Based Models in R

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

4 hours

Machine Learning Fundamentals in R

Dimensionality Reduction in R

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

4 hours

Support Vector Machines in R

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

4 hours

Fundamentals of Bayesian Data Analysis in R

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

4 hours

Hyperparameter Tuning in R

Learn how to tune your model's hyperparameters to get the best predictive results.

4 hours

Bayesian Regression Modeling with rstanarm

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

4 hours

Predicting Movie Rental Durations

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

2 hours

Introduction to Spark with sparklyr in R

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

4 hours

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Training 2 or more people?

Cadastre-se mais 13,700,000 Alunos e comece Cientista de aprendizado de máquina com R Hoje!