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.
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machine learning, R programming, data science, statistical modeling, artificial intelligence, supervised learning, unsupervised learning, deep learning, data analysis, predictive analytics, neural networks, regression analysis, Chapman & Hall, feature engineering, algorithm implementation
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