Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Machine Learning with R Quick Start Guide

You're reading from Machine Learning with R Quick Start Guide A beginner's guide to implementing machine learning techniques from scratch using R 3.5

Product type Paperback

Published in Mar 2019

Publisher Packt

ISBN-13 9781838644338

Length 250 pages

Edition 1st Edition

Languages

R

Tools

RStudio

Concepts

Machine Learning

Author (1):

Iván Pastor Sanz

View More author details

Table of Contents (9) Chapters

Preface

1. R Fundamentals for Machine Learning FREE CHAPTER

2. Predicting Failures of Banks - Data Collection

3. Predicting Failures of Banks - Descriptive Analysis

4. Predicting Failures of Banks - Univariate Analysis

5. Predicting Failures of Banks - Multivariate Analysis

6. Visualizing Economic Problems in the European Union

7. Sovereign Crisis - NLP and Topic Modeling

8. Other Books You May Enjoy

Leave a review - let other readers know what you think

Summary

In this chapter, we saw how univariate analysis reduced the sample space of our problem data and analyzed the data. Consequently, in the next chapter, we will see how these variables can be combined to obtain an accurate model, where several algorithms will be tested.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at €18.99/month. Cancel anytime

Authors (1)

Sanz

Sanz

Ivn Pastor Sanz is a lead data scientist and machine learning enthusiast with extensive experience in finance, risk management, and credit risk modeling. Ivn has always endeavored to find solutions to make banking more comprehensible, accessible, and fair. Thus, in his thesis to obtain his PhD in economics, Ivn tried to identify the origins of the 2008 financial crisis and suggest ways to avoid a similar crisis in the future.

See other products by Sanz

Other recommended products

Related to this chapter

Ensemble Machine Learning Cookbook

Ensemble Machine Learning Cookbook

This book uses a recipe-based approach to showcase the power of machine learning algorithms to build ensemble models using Python libraries. Through this book, you will be able to pick up the code, understand in depth how it works, execute and implement it efficiently. This will be a desk reference to implement a wide range of tasks and solve the common and uncommon problems in ensemble machine learning domain.

Jan 2019 11h 12m

Machine Learning with R Cookbook

Machine Learning with R Cookbook

The R language is a powerful open source functional programming language. At its core, R is a statistical language that provides impressive tools to analyze data and create high-level graphics. This book covers the basics of R by setting up a user-friendly programming environment and programming ETL in R. Data exploration examples are provided that demonstrate how powerful data visualisation and machine learning is in discovering hidden relationships. You will also explore air quality data, steps to fix the missing values and visualising the same. You will then dive into important machine learning topics, including data classification, regression, survival analysis, time series analysis, clustering association rule mining, and dimension reduction.This book will include the latest code and examples based on R 3.3 and above—updated for better computation, accuracy, and speed with R.

Oct 2017 19h 4m

Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R

This book introduces you to time series analysis and forecasting with R; this is one of the key fields in statistical programming and includes techniques for analyzing data to extract meaningful insights. You will explore methods, such as prediction with time series analysis, and identify the relationship between each data point in the series.

May 2019 14h 56m

This book will empower you to produce and present impressive analyses from data, by selecting and implementing the appropriate data mining techniques in R. Explore a data mining crime case, where you will be requested to help resolving a real fraud case affecting a commercial company, by the mean of both basic and advanced data mining techniques.

Nov 2017 14h 44m

Mastering Machine Learning with R

Mastering Machine Learning with R

Machine learning is the field of Artificial Intelligence where we build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2.

Apr 2017 14h 0m

Neural Networks with R

Neural Networks with R

The book helps you learn neural networks and implement them in R. It covers real-world use cases that will help you better understand their concepts. A basic understanding of R and mathematics is required.

Applied Supervised Learning with R

Applied Supervised Learning with R

Applied Supervised Learning with R will make you a pro at identifying your business problem, selecting the best supervised machine learning algorithm to solve it, and fine-tuning your model to exactly deliver your needs without overfitting itself.

May 2019 16h 44m

Learning Quantitative Finance with R

Learning Quantitative Finance with R

This book covers applications of quantitative finance in R. It starts with the basics of quantitative finance and goes to complexity at the end of the book along with a varying degree of R complexity. This will guide you to implement different trading strategies for various financial instruments using basic to complex techniques along with its optimization and keeping the risk of financial instruments in check.

Mar 2017 9h 28m

Hands-On Ensemble Learning with R

Hands-On Ensemble Learning with R

This book introduces you to the concept of ensemble learning and demonstrates how different machine learning algorithms can be combined to build efficient machine learning models. Use R to implement the popular trilogy of ensemble techniques, i.e. bagging, random forest and boosting, to build faster and more accurate machine learning models.

Jul 2018 12h 32m

Statistical Application Development with R and Python

Statistical Application Development with R and Python

Statistical Analysis involves collecting and examining data to describe the nature of data that needs to be analyzed. It helps you explore the relation of data and build models to make better decisions. You will begin with a brief understanding of the nature of data and end with modern and advanced statistical models like CART. Every step is taken with DATA and R code, and further enhanced by Python. By the end of this book you will be able to apply your statistical learning in major domains at work or in your projects.

Aug 2017 14h 24m

R Machine Learning Projects

R Machine Learning Projects

The purpose of the book is to help a machine learning practitioner gets hands-on experience in working with real-world data and apply modern machine learning algorithms. You will learn to implement each algorithm to a specific industry problem. It covers projects involving both supervised as well as unsupervised learning approaches.

Jan 2019 11h 8m

Mastering Machine Learning with R

Mastering Machine Learning with R

Machine learning is a field of AI where we build systems that learn from data. This book explains complicated concepts with real-world applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints. Finally, it will walk you through topics such as text analysis, time series, and deep learning.

Jan 2019 11h 48m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.