This is the code repository for Hands-On Data Analytics with R [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
This course will expand your understanding of statistics so you can* create analytic models in R. High-level data science techniques will be presented to you in a practical manner, to help you bridge the gap between the questions you wish to answer, the data used for analysis, and how to create some of the classic models used in data analytics.
- Utilize a variety of R's machine learning and statistical techniques, interpret their outputs, and present these insights effectively and with confidence
- Use dimensionality reduction to overcome this issue without too many explanatory variables
- Mine data with common techniques such as hierarchical and K-means clustering
- Approach data using inferential statistics to implement effective hypothesis-testing techniques, providing strong evidence for a claim about your data
- Implement popular predictive analytic techniques that allow for the extraction of deep and hidden patterns within data
- Ensure that the models and techniques used are appropriate; checking a model's effectiveness and reliability will make you confident in its predictive capabilities
- Discover neat and visually effective ways of presenting your findings and predictions
To fully benefit from the coverage included in this course, you will need:
This course is for people from the business and scientific sectors who would like to broaden their data analytic capabilities using R. Having a working knowledge of R as well as basic understanding of statistics is assumed.
This course has the following software requirements:
SETUP AND INSTALLATION
Minimum Hardware Requirements
For successful completion of this course, students will require the computer systems with at least the following:
OS: R runs on Windows, OS X and a “wide variety of Unix platforms”
Processor: 32 or 64 bit Single core
Memory: 32MB
Storage: 1MB
Recommended Hardware Requirements For an optimal experience with hands-on labs and other practical activities, we recommend the following configuration:
OS: It runs on Windows, OS X and a “wide variety of Unix platforms”
Processor: 32 or 64 bit Single Core
Memory: 1GB
Storage: 1MB
Software Requirements
Operating system: It runs on Windows, OS X and a “wide variety of Unix platforms”
Browser: A network connection for data recovering over network
The latest version of R (version 3.3.3) Installed: https://cran.r-project.org/
The administrative privileges are required to install and run RStudio utilities under Windows 2000/XP/2003/Vista/7/8/2012 Server/8.1/10
RStudio Desktop IDE, Open Source Latest Version: https://www.rstudio.com/products/rstudio/
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