Machine Learning in R & Predictive Models | 3 Courses in 1

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

Created by: Kate Alison
GIS & Data Science

Created by: Georg Müller
Data Science Experte

What Will I 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
• You'll have a copy of the scripts used in the course for your reference to use in your analysis

Requirements

• Availability computer and internet & strong interest in the topic

Target audience

• 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