Machine Learning with R
Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data
Created by Brett Lantz
Explore practical machine learning techniques using R, from preparing raw data to building and improving predictive models. You will work with real-world datasets and learn how to handle big data, evaluate models, and apply advanced methods. Gain hands-on experience that helps you confidently tackle data science challenges.
Packt | May 2023 | 762 min
What You Will Learn
You will build your skills step by step, starting with data preparation and moving through a range of modeling techniques. Along the way, you'll use R's most up-to-date libraries and tools, practice with real datasets, and explore both foundational and advanced machine learning methods. Each topic is explained clearly, with practical examples to reinforce your understanding.
Key Features
- Master data preparation, feature engineering, and advanced modeling in R
- Apply ensemble methods and model evaluation to improve prediction accuracy
- Work efficiently with big data using parallel computing and GPU resources
Target Audience
Ideal for data scientists, analysts, and students with some programming or statistics background who want to deepen their machine learning skills in R. If you are looking to solve real problems, improve your models, and work confidently with large or complex datasets, this course is designed for you.
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