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Key benefits

Advance your ML career with the help of detailed explanations, intuitive illustrations, and code examples

Gain practical insights into the real-world applications of statistics and machine learning

Explore the technicalities of statistics and machine learning for effective data presentation

Purchase of the print or Kindle book includes a free PDF eBook

Description

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.

Who is this book for?

This book is for beginner to intermediate-level data scientists, undergraduate to masters-level students, and early to mid-senior data scientists or analysts looking to expand their knowledge of machine learning by exploring various R libraries. Basic knowledge of linear algebra and data modeling is a must.

What you will learn

Hone your skills in different probability distributions and hypothesis testing

Explore the fundamentals of linear algebra and calculus

Master crucial statistics and machine learning concepts in theory and practice

Discover essential data processing and visualization techniques

Engage in interactive data analysis using R

Use R to perform statistical modeling, including Bayesian and linear regression

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Frequently bought together

€37.99

The Statistics and Machine Learning with R Workshop

€37.99

€37.99

Total € 113.97

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Shipping Details

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Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

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Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

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Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

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Unfortunately, due to several restrictions, we are unable to ship to the following countries:

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Amazon verified reviews

Sangita Mahala Nov 27, 2023

This book is a highly recommended resource for anyone seeking a comprehensive and practical introduction to statistics and machine learning using R. Peng Liu's masterful guidance and engaging approach make this book an essential tool for data scientists of all levels.

Amazon Verified review

Steven Fernandes Dec 05, 2023

The book expertly bridges theory and practice in statistics and machine learning, focusing on R for practical application. It starts with probability distributions and hypothesis testing, building a foundation in linear algebra and calculus. The book excels in making complex statistical and machine learning concepts accessible, emphasizing data processing and visualization techniques. Interactive data analysis using R is a key feature, enhancing engagement and understanding. The detailed coverage of statistical modeling, including Bayesian and linear regression in R, makes it an indispensable resource for those aspiring to master data analysis in a hands-on, applied manner.

Gustavo Feb 29, 2024

I have received this book from Packt to provide my review. The book has a good R foundation for those who are not familiar with the Language. It also brings a couple of Math/ Algebra/ Calculus chapters that don't have very strong application examples, but it's interesting and well explained.The Stats portion in the last part is very good, with many regression examples.Great book.

Papu Siameja Feb 06, 2024

The combination of a little bit of theory and practical examples makes this book a good introduction to the use of R for statistical analysis and machine learning. The examples are clear and easy to follow as the required R packages are clearly stated at the beginning of each chapter.

Feefo Verified review

H2N Nov 16, 2023

This book is an excellent introduction for early-career data scientists and undergraduate students with a basic grasp of linear algebra and modeling. It starts with the essentials of R programming, focusing on key data structures and logical operations. The journey continues with data processing techniques using dplyr, covering transformations and aggregations. The reader is then guided through more complex data processing and quality enhancement methods. Data visualization is masterfully explained through ggplot2, from elementary to sophisticated techniques. The book also delves into exploratory data analysis, R Markdown for interactive documents, and advanced topics such as linear algebra, calculus in R, probability, statistical estimation, and regression models, finishing with Bayesian statistics. This comprehensive guide is invaluable for practical R applications in data science, though readers may long for a Python version.

The Statistics and Machine Learning with R Workshop: Unlock the power of efficient data science modeling with this hands-on guide

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