by Rahul Tiwari | Released March 2019 | ISBN: 9781789134667

Explore a variety of statistical and Machine Learning techniques using RAbout This VideoAccelerate your data analytic capabilities from a basic understanding to being able to apply and interpret results effectively, providing deep insight into a plethora of data-driven scenariosContains the maximum amount of practical examples and mini-tests with minimal lecturing to encourage a natural and self-rewarding progressionPerform and interpret results from the most commonly used statistical and ML techniques used by data professionals such as linear models, k-means clustering, and Principal Component Analysis.In DetailThis 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.You will start off by understanding dimensionality reduction and data mining in R and learning how to simplify complex datasets and unearth patterns from data. Moving on, you will understand hypothesis testing and p-values. You will also demonstrate one-sample and two-sample tests and the benefits they provide as very sophisticated analytical techniques. You will understand how data can give you predictive insights into the future and will conclude by presenting data in a way that will allow you to answer questions with data-driven confidence.By the end of the course, you will be capable of utilizing R's statistical prowess to analyze a variety of datasets and present these insights effectively.All the code files for this course are available on Github at - https://github.com/PacktPublishing/Hands-On-Data-Analytics-with-R--V-Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you. Show and hide more

1. Chapter 1 : Dimensionality Reduction in R
   • The Course Overview 00:03:46
   • Using Dimensionality Reduction 00:08:25
   • Principal Component Analysis 00:07:52
   • Using Principal Components 00:04:18
2. Chapter 2 : Data Mining Using R
   • Cluster Analysis Technique 00:04:09
   • K-Means Clustering 00:11:29
   • Hierarchical Clustering 00:08:23
3. Chapter 3 : Inferential Statistics
   • Hypothesis Testing and P-Value 00:06:25
   • One-Sample T-Test 00:10:17
   • Two-Sample T-test 00:08:05
   • Two-Sample T-Test (Unpaired) 00:10:41
4. Chapter 4 : Predictive Analytics with R
   • Regression and Classification Techniques 00:03:14
   • Classification Trees 00:14:25
   • Linear Regression 00:12:02
5. Chapter 5 : Checking and Presenting Results
   • Model Checks in R 00:04:19
   • Model Predictions 00:04:42
   • Interacting with Data Using rCharts 00:06:30
   • Shiny Dashboards 00:06:48
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