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  • Book Overview & Buying The Statistics and Machine Learning with R Workshop
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The Statistics and Machine Learning with R Workshop

The Statistics and Machine Learning with R Workshop

By : Liu Peng
4.6 (5)
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The Statistics and Machine Learning with R Workshop

The Statistics and Machine Learning with R Workshop

4.6 (5)
By: Liu Peng

Overview of this book

The Statistics and Machine Learning with R Workshop is a comprehensive resource packed with insights into statistics and machine learning, along with a deep dive into R libraries. The learning experience is further enhanced by practical examples and hands-on exercises that provide explanations of key concepts. Starting with the fundamentals, you’ll explore the complete model development process, covering everything from data pre-processing to model development. In addition to machine learning, you’ll also delve into R's statistical capabilities, learning to manipulate various data types and tackle complex mathematical challenges from algebra and calculus to probability and Bayesian statistics. You’ll discover linear regression techniques and more advanced statistical methodologies to hone your skills and advance your career. By the end of this book, you'll have a robust foundational understanding of statistics and machine learning. You’ll also be proficient in using R's extensive libraries for tasks such as data processing and model training and be well-equipped to leverage the full potential of R in your future projects.
Table of Contents (20 chapters)
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1
Part 1:Statistics Essentials
8
Part 2:Fundamentals of Linear Algebra and Calculus in R
12
Part 3:Fundamentals of Mathematical Statistics in R

Probability Basics

Probability distribution is an essential concept in statistics and machine learning. It describes the underlying distribution that governs the generation of potential outcomes or events in an experiment or random process. There are different types of probability distributions, depending on the specific domain and characteristics of the data. A proper probability distribution is a useful tool in understanding and modeling the behavior of random processes and events, providing convenient tools for decision-making and predictions when developing data-driven predictive and optimization models.

By the end of this chapter, you will understand the common probability distributions and their parameters. You will also be able to use these probability distributions to perform usual tasks such as sampling and probability calculations in R, as well as common sampling distribution and order statistics.

In this chapter, we will cover the following topics:

  • Introducing...
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The Statistics and Machine Learning with R Workshop
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