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Machine Learning Fundamentals in R

更新时间 2026年3月
Predict categorical and numeric responses via classification and regression, and discover the hidden structure of datasets with unsupervised learning.
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学习路径描述

Machine Learning Fundamentals in R

Learn the basics of prediction using machine learning. This track covers predicting categorical and numeric responses via classification and regression, and discovering the hidden structure of datasets (unsupervised learning). Learn how to process data for modeling, how to train your models, how to visualize your models and assess their performance, and how to tune their parameters for better performance.

先决条件

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  • Course

    1

    Supervised Learning in R: Classification

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

  • Course

    2

    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.

  • Project

    额外

    Predict Future Sales of Fast-Food Menu Items

    Help a fast food chain save money and place more accurate orders by building a model to predict food sales.

  • Course

    4

    Unsupervised Learning in R

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

Machine Learning Fundamentals in R
6 课程
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