Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series)

Description

Machine Learning with R: Hands-On Guide to Data Science & AI

Machine Learning with R is your complete guide to mastering machine learning concepts using the R programming language. This book provides practical examples, real-world datasets, and step-by-step tutorials to help you build predictive models, analyze data, and optimize algorithms.

What You’ll Learn in This Machine Learning with R Course

• Fundamentals of Machine Learning and Statistical Modeling
• Data Preprocessing, Cleaning, and Feature Engineering
• Supervised Learning: Regression and Classification Techniques
• Unsupervised Learning: Clustering and Dimensionality Reduction
• Model Evaluation, Hyperparameter Tuning, and Performance Metrics
• Deep Learning and Neural Networks with R
• Using R Packages for Machine Learning: caret, randomForest, xgboost, and more

Who Should Take This Course?

This book is designed for:

• Data scientists and analysts looking to enhance their machine learning skills
• R programmers interested in data science applications
• Students and professionals preparing for AI and ML careers
• Anyone who wants to apply Machine Learning with R in real-world projects

Course Requirements

Prior knowledge of R programming is recommended but not required. Basic understanding of statistics and data analysis concepts will be helpful.

Explore These Valuable Resources

• caret Package for Machine Learning
• R Community and Publications
• Deep Learning with R & TensorFlow

Explore Related Courses

• Machine Learning Courses
• R Programming Training
• Data Science & AI Courses
• Deep Learning with R
• Statistical Modeling with R

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