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

Machine Learning in R & Predictive Models |Theory & Practice

My course will be your complete guide to the theory and applications of supervised & unsupervised machine learning and predictive modelling using the R–programming language. This course also combines the material of 3 independent courses related to (1) R–programming, (2) Machine Learning and (3) Predictive modelling.

Unlike other courses, it offers NOT ONLY the guided demonstrations of the R–scripts but also covers theoretical background that will allow you to FULLY UNDERSTAND & APPLY MACHINE LEARNING & PREDICTIVE MODELS (K–means, Random Forest, SVM, logistic regression, etc) in R (many R packages incl. caret package will be covered).

This course also covers all the main aspects of practical and highly applied data science related to Machine Learning (classification & regressions) and unsupervised clustering techniques. Thus, if you take this course, you will save lots of time & money on other expensive materials in the R based Data Science and Machine Learning domain.

In this age of big data, companies across the globe use R to analyze big volumes of data for business and research. By becoming proficient in supervised & unsupervised machine learning and predictive modeling in R, you can give your company a competitive edge and boost your career to the next level