While choosing the best programming language for data science, two of the most popular languages around, R and Python come to mind but choosing between them is always a dilemma for a data scientist.But the main point is deep understanding of the algorithms and their application can be in any language of choice.
In this series of articles on Machine Learning in R we delve into fundamentals of Machine Learning and the various algorithms needed.
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A Guide to Machine Learning in R for Beginners- Part 1
In the first part, we learn about the building blocks of Machine Learning: Statistics. -
A Guide to Machine Learning in R for Beginners- Part 2
In the second part, we learn about downloading and installing the R statistical language -
A Guide to Machine Learning in R for Beginners- Part 3
In the third part, we discuss basic operations in R.We also delve into Exploratory Data Analysis in R -
A Guide to Machine Learning in R for Beginners- Part 4
In this part , we get to know about functions , models and hypothesis. We also study in detail about Linear Regression with code in R -
A Guide to Machine Learning in R for Beginners- Part 5
In this part, we discuss in detail about Logistic Regression in R. -
A Guide to Machine Learning in R for Beginners- Part 6
In this part, we discuss in detail about Decision Trees in R with an example
An overview of the R visualisation capabilities.
