Machine Learning in R & Predictive Models |Theory & Practice

Supervised & unsupervised machine learning in R, clustering in R, predictive models in R by many labs, understand theory

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

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 Machine Learning On Real-World Data