Leveled Texts for Mathematics

With a focus on number and operations, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different read

With a focus on algebra, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different reading levels, ac

With a focus on geometry, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different reading levels, a

With a focus on measurement, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different reading levels

With a focus on fractions, decimals, and percents, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four di

With a focus on data analysis and probability, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four differ

With a focus on biology, a guide to using leveled texts to differentiate instruction in life sciences offers fifteen different topics with high-interest text written at four different reading levels,

With a focus on physical science, a guide to using leveled texts to differentiate instruction in science offers fifteen different topics with high-interest text written at four different reading level

With a focus on the world history and cultures, a guide to using leveled texts to differentiate instruction in social studies offers fifteen different topics with high-interest text written at four di

With a focus on the colonial period, a guide to using leveled texts to differentiate instruction in American history offers fifteen different topics with high-interest text written at four different r

Fountas & Pinnell take you through every aspect of leveled books from how to select and use them for different instructional purposes to prototype descriptions for fiction and nonfiction books at eac

Increase student comprehension through in-depth examinations of content-area texts.This comprehensive resource provides teachers with leveled question stems at four different content-areas for student

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every cha

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every cha

Developed in conjunction with Lesley University, this engaging resource for first grade provides effective, research-based strategies to help teachers differentiate problem solving in the classroom. I

This classroom resource for Level 3 provides effective, research-based strategies to help teachers differentiate problem solving in the classroom and includes: 50 leveled math problems (150 problems t

Developed in conjunction with Lesley University, this engaging resource for fourth grade provides effective, research-based strategies to help teachers differentiate problem solving in the classroom.

This classroom resource for Level 2 provides effective, research-based strategies to help teachers differentiate problem solving in the classroom and includes: 50 leveled math problems (150 problems t

An engagingly-written account of mathematical tools and ideas, this book provides a graduate-level introduction to the mathematics used in research in physics. The first half of the book focuses on the traditional mathematical methods of physics – differential and integral equations, Fourier series and the calculus of variations. The second half contains an introduction to more advanced subjects, including differential geometry, topology and complex variables. The authors' exposition avoids excess rigor whilst explaining subtle but important points often glossed over in more elementary texts. The topics are illustrated at every stage by carefully chosen examples, exercises and problems drawn from realistic physics settings. These make it useful both as a textbook in advanced courses and for self-study. Password-protected solutions to the exercises are available to instructors at www.cambridge.org/9780521854030.

This book is designed for a first course in numerical analysis. It differs considerably from other such texts in its choice of topics.