Getting Started with Machine Learning in R [Video]
This is the code repository for Getting Started with Machine Learning in R [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
About the Video Course
Do you want to turn your data to predict outcomes that make real impact and have better insights? R provides a cutting-edge power you need to work with machine learning techniques You will learn to apply machine learning techniques in the popular statistical language R. This course will get you started with Machine Learning and R by understanding Machine Learning and installing R. The course will then take you through some different types of ML. You will work with a classic dataset using Machine Learning. You will learn Linear and Logistic Regression algorithms and analyze the dataset. The course will take you through algorithms like Random Forest and Naive Bayes for working on your data in R. You will then see some of the excellent graphical tools in R, and some discussion of the goals and techniques for presenting graphical data. Analysis of the data set is demonstrated from end to end, with example R code you can use. Then you’ll have a chance to do it yourself on another data set. By the end of the course you will learn how to gain insights from complex data and how to choose the correct algorithm for your specific needs.
What You Will Learn
- Process a classic dataset, from data cleaning to presenting results with effective graphics.
- Explore different types of ML
- Clean your dataset and run a linear regression fit
- Use ML on your dataset by running a random forest algorithm
- Run naive Bayes algorithm on your dataset
- Present graphical information about your dataset
- Use the different packages of R to represent your data
Instructions and Navigation
Assumed Knowledge
To fully benefit from the coverage included in this course, you will need:
This course is for aspiring data scientists who are familiar with the basics of the R language and data frames, and have a basic knowledge of statistics. You are not expected to have any knowledge of machine-learning systems. If you are looking to understand how the R programming environment and packages can be used to develop machine learning systems, then this is the perfect course for you.
Technical Requirements
This course has the following software requirements:
- IDE : R Studio
- Notepad++
- Browser : Chrome or equivalentt Version
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