Supervised Machine Learning for Text Analysis in R (Chapman & Hall/CRC Data Science Series) - Image 1

£52.24

CRC Press Supervised Machine Learning for Text Analysis in R (Chapman & Hall/CRC Data Science Series)

Name: Supervised Machine Learning for Text Analysis in R (Chapman & Hall/CRC Data Science Series)
Brand: CRC Press
Price: 52.24 GBP
Availability: InStock

Data Mining

About as cheap as it gets. The only time it was cheaper was 2 months ago.

£52 today · all-time low £52 (May 2026) · usually £52

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 69 days · 69 data points (no recent data)

Historical

Generating forecast…

Price Distribution

Price distribution over 69 days • 2 price levels

Days at Price

Current Price

Price Analysis

Most common price: £52 (35 days, 50.7%)

Price range: £52 - £53

Price levels: 2 different prices over 69 days

Description

Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.

Product Specifications

Brand: CRC Press
Format: paperback
ASIN: 0367554194
Category: Books > Subjects > Computing & Internet > Databases > Data Storage & Management > Data Mining
Domain: Amazon UK
Release Date: 22 October 2021
Listed Since: 22 April 2021

Barcode

No barcode data available

CRC Press Supervised Machine Learning for Text Analysis in R (Chapman & Hall/CRC Data Science Series)

About as cheap as it gets. The only time it was cheaper was 2 months ago.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Text Mining with Machine Learning: Principles and Techniques

Semisupervised Learning for Computational Linguistics (Chapman & Hall/CRC Computer Science & Data Analysis)

Natural Language Processing and Text Mining

Machine Learning for Text

Machine Learning for Text

Text Mining: Applications and Theory

Natural Language Processing: Python and NLTK: Learn to build expert NLP and machine learning projects using NLTK and other Python libraries

Python Natural Language Processing: Advanced machine learning and deep learning techniques for natural language processing

Python for Natural Language Processing: Programming with NumPy, scikit-learn, Keras, and PyTorch (Cognitive Technologies)

Large Language Model Crash Course: Hands on With Python (Mastering Machine Learning)

Natural Language Analytics with Generative Large-Language Models: A Practical Approach with Ollama and Open-Source LLMs (SpringerBriefs in Computer Science)

Text Mining with MATLAB®

Natural Language Processing and Applications

Natural Language Processing in Artificial Intelligence ― NLPinAI 2021: 999 (Studies in Computational Intelligence, 999)

Recent Advances in NLP: The Case of Arabic Language: 874 (Studies in Computational Intelligence, 874)

Corpus Linguistics and Linguistically Annotated Corpora

Natural Language Processing: A Machine Learning Perspective

Natural Language Processing Tools: Developing a Part-of-Speech Tagger and Partial Dependency Parser for Irish

Building Applications with Large Language Models: Techniques, Implementation, and Applications