Integrated IScience: Science Notebook Course 2 - JH.

Integrated IScience: Science Notebook Course 2 - JH. PDF Author:
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 224

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Integrated IScience: Science Notebook Course 2 - JH.

Integrated IScience: Science Notebook Course 2 - JH. PDF Author:
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 224

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Book Description


Integrated IScience: Science Notebook Course 3 - JH.

Integrated IScience: Science Notebook Course 3 - JH. PDF Author:
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 240

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Integrated Science

Integrated Science PDF Author: Glencoe/McGraw-Hill
Publisher:
ISBN: 9780078924712
Category : Earth sciences
Languages : en
Pages : 795

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Integrated IScience

Integrated IScience PDF Author:
Publisher:
ISBN: 9780076840694
Category : Science
Languages : en
Pages :

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Integrated iScience, Course 3, Student Edition

Integrated iScience, Course 3, Student Edition PDF Author: McGraw-Hill Education
Publisher: McGraw-Hill Education
ISBN: 9780076772872
Category : Science
Languages : en
Pages : 976

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Book Description
Integrated iScience print student edition.

Integrated Science Course 2

Integrated Science Course 2 PDF Author:
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 161

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Life i Science

Life i Science PDF Author: Glencoe/McGraw-Hill
Publisher:
ISBN: 9780078914850
Category : Earth sciences
Languages : en
Pages : 420

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Book Description
Includes resources on classroom and laboratory management and safety, differentiated instruction, English-language learners, language arts and literacy, mathematics support, school-to-home connection, and performance assessment.

Physical IScience

Physical IScience PDF Author: Glencoe/McGraw-Hill
Publisher:
ISBN: 9780078925047
Category : Earth sciences
Languages : en
Pages : 825

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Book Description
"IScience meets students where they are through engaging features and thought-provoking questions that encourage them to relate the science concepts to the world around them. The inquiry-based 5E lesson cycle provides active, hands-on explorations of the concepts to the world around them"--Publisher Website.

The Cambridge Handbook of Group Interaction Analysis

The Cambridge Handbook of Group Interaction Analysis PDF Author: Elisabeth Brauner
Publisher: Cambridge University Press
ISBN: 1108655165
Category : Psychology
Languages : en
Pages : 968

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Book Description
This Handbook provides a compendium of research methods that are essential for studying interaction and communication across the behavioral sciences. Focusing on coding of verbal and nonverbal behavior and interaction, the Handbook is organized into five parts. Part I provides an introduction and historic overview of the field. Part II presents areas in which interaction analysis is used, such as relationship research, group research, and nonverbal research. Part III focuses on development, validation, and concrete application of interaction coding schemes. Part IV presents relevant data analysis methods and statistics. Part V contains systematic descriptions of established and novel coding schemes, which allows quick comparison across instruments. Researchers can apply this methodology to their own interaction data and learn how to evaluate and select coding schemes and conduct interaction analysis. This is an essential reference for all who study communication in teams and groups.

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch PDF Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624

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Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala