English is a hybrid of Greek, Latin and some ten other languages, which can make tracing a word's meaning pretty difficult. Now, with this classic reference for students of the English language, perfect for word fanatics, puzzlers and writers, 'Word Stems' defines and deciphers thousands of the most commonly used foreign words that form the foundation of our English words.

A Valuable Classroom Tool: Separate sections on Latin and Greek derivations. Each section has 20 lessons—with assignments following each lesson—giving the user a vast technical vocabulary and increased word-recognition ability. A Definitive Reference: Hundreds of Greek and Latin stems, prefixes, and suffixes show the precise application of the classical languages to biological and medical usage. Topic-organized bibliography, index of bases.

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.

Horace G. Danner’s A Thesaurus of English Word Roots is a compendium of the most-used word roots of the English language. As Timothy B. Noone notes in his foreword: “Dr. Danner’s book allows you not only to build up your passive English vocabulary, resulting in word recognition knowledge, but also gives you the rudiments for developing your active English vocabulary, making it possible to infer the meaning of words with which you are not yet acquainted. Your knowledge can now expand and will do so exponentially as your awareness of the roots in English words and your corresponding ability to decode unfamiliar words grows apace. This is the beginning of a fine mental linguistic library: so enjoy!” In A Thesaurus of English Word Roots, all word roots are listed alphabetically, along with the Greek or Latin words from which they derive, together with the roots’ original meanings. If the current meaning of an individual root differs from the original meaning, that is listed in a separate column. In the examples column, the words which contain the root are then listed, starting with their prefixes, for example, dysacousia, hyperacousia. These root-starting terms then are followed by terms where the root falls behind the word, e.g., acouesthesia and acoumeter. These words are followed by words where the root falls in the middle or the end, as in such terms as bradyacusia and odynacusis.. In this manner, A Thesaurus of English Word Roots places the word in as many word families as there are elements in the word. This work will interest linguists and philologists and anyone interested in the etymological aspects of English language.

Presents an overview of the development of the English language and examines the formation of words especially from Greek and Latin roots. Also discusses definitions and usage.

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This picture word ebook of 1000 first science words is the perfect STEM ebook for helping children learn. It introduces key scientific concepts while broadening children's vocabulary and strengthening their early reading and writing skills. Every picture-packed page is full of things such as sounds, light, senses, and machines, with words for each image. 1000 Words: STEM clearly labels each picture, which encourages picture-and-word association and helps early reading. Each topic features questions that ask children to find things on the page or that stimulate thinking, talking, and early science skills. The words have been chosen with the help of a leading educational consultant, and include lots of useful nouns, plus some interesting adjectives, and common verbs. This fun and educational picture word ebook is a must-have first reference title for parents who are keen to develop their child's language, science, and literacy skills.