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Machine with R

Track :

Programming

Lessons no : 30

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What will you learn in this course?
  • Develop and implement machine learning algorithms using R for real-world data analysis and prediction tasks
  • Apply R programming skills to preprocess, clean, and visualize data for machine learning projects
  • Evaluate model performance and select appropriate algorithms for classification, regression, and clustering tasks in R
  • Utilize R packages like caret, randomForest, and e1071 to build and tune machine learning models effectively
  • Interpret machine learning results to derive actionable insights and support data-driven decision making
  • Design and execute end-to-end machine learning workflows in R for various industry applications
  • Identify and address common challenges in machine learning such as overfitting, bias, and data imbalance using R tools
  • Leverage R for feature engineering and selection to improve model accuracy and efficiency
  • Implement cross-validation and hyperparameter tuning techniques in R to optimize machine learning models
  • Communicate complex machine learning concepts and results clearly to technical and non-technical audiences

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  • Watch All Lessons
  • Watch at least 50% of Lesson Duration
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  • The Certificate is free !
Lessons | 30


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Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning .