What you’ll learn
- Your complete guide to unsupervised & supervised machine learning and predictive modeling using R-programming language
- It covers both theoretical background of MACHINE LERANING & and predictive modeling as well as practical examples in R and R-Studio
- Fully understand the basics of Machine Learning, Cluster Analysis & Predictive Modelling
- Highly practical data science examples related to supervised machine learning, clustering & prediction modelling in R
- Learn R-programming from scratch: R crash course is included that you could start R-programming for machine learning
- Be Able To Harness The Power of R For Practical Data Science
- Compare different different machine learning algorithms for regression & classification modelling
- Apply statistical and machine learning based regression & classification models to real data
- Build machine learning based regression & classification models and test their robustness in R
- Learn when and how machine learning & predictive models should be correctly applied
- Test your skills with multiple coding exercices and final project that you will ommplement independently
- Implement Machine Learning Techniques/Classification Such As Random Forests, SVM etc in R
Who this course is for:
- The course is ideal for professionals who need to use cluster analysis, unsupervised machine learning and R in their field.
- Everyone who would like to learn Data Science Applications In The R & R Studio Environment
- Everyone who would like to learn theory and implementation of Unsupervised Learning On Real-World Data
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