Author: Megan Kortlandt
Publisher: ASCD
ISBN: 1416630457
Category : Education
Languages : en
Pages : 167
Book Description
Megan Kortlandt, Carly Stone, and Samantha Keesling have developed a flexible structure for collaborative professional learning that they call the principal lab, in which K–12 principals learn with and from each other to become better instructional leaders. Each chapter walks through the foundational components of a successful principal lab—relationship building, anchoring experiences, observations, and feedback—and then discusses how to lay the groundwork, figure out logistics, and plan and structure labs. Principal Labs: Strengthening Instructional Leadership Through Shared Learning combines the latest research in adult learning with the authors' practical experience to discuss the qualities of a successful principal lab and provide the tools to build your own. It's easy to get started with downloadable reflection and observation templates based on the examples in each chapter. As a school principal you have many responsibilities, and finding time for your own professional development can be a challenge. The approach in this book will help you effectively use your time to connect with other principals, practice and develop feedback skills, and ultimately make informed decisions for instructional improvement in your school.
Principal Labs
Principal Labs
Author: Megan Kortlandt
Publisher:
ISBN: 9781760942618
Category : Laboratory schools
Languages : en
Pages : 0
Book Description
Publisher:
ISBN: 9781760942618
Category : Laboratory schools
Languages : en
Pages : 0
Book Description
GAO Report on the Department of Energy National Laboratory Management
Author: United States. Congress. House. Committee on Science. Subcommittee on Basic Research
Publisher:
ISBN:
Category : Political Science
Languages : en
Pages : 1116
Book Description
Publisher:
ISBN:
Category : Political Science
Languages : en
Pages : 1116
Book Description
Department of Energy uncertain progress in implementing national laboratory reforms : report to Congressional requesters
Author:
Publisher: DIANE Publishing
ISBN: 142897573X
Category :
Languages : en
Pages : 62
Book Description
Publisher: DIANE Publishing
ISBN: 142897573X
Category :
Languages : en
Pages : 62
Book Description
Forum for Applied Research and Public Policy
Author:
Publisher:
ISBN:
Category : Policy sciences
Languages : en
Pages : 448
Book Description
Publisher:
ISBN:
Category : Policy sciences
Languages : en
Pages : 448
Book Description
Code of Federal Regulations
Author:
Publisher:
ISBN:
Category : Administrative law
Languages : en
Pages : 818
Book Description
Special edition of the Federal Register, containing a codification of documents of general applicability and future effect ... with ancillaries.
Publisher:
ISBN:
Category : Administrative law
Languages : en
Pages : 818
Book Description
Special edition of the Federal Register, containing a codification of documents of general applicability and future effect ... with ancillaries.
The Code of Federal Regulations of the United States of America
Author:
Publisher:
ISBN:
Category : Administrative law
Languages : en
Pages : 768
Book Description
The Code of Federal Regulations is the codification of the general and permanent rules published in the Federal Register by the executive departments and agencies of the Federal Government.
Publisher:
ISBN:
Category : Administrative law
Languages : en
Pages : 768
Book Description
The Code of Federal Regulations is the codification of the general and permanent rules published in the Federal Register by the executive departments and agencies of the Federal Government.
Principles and Labs for Deep Learning
Author: Shih-Chia Huang
Publisher: Academic Press
ISBN: 0323901999
Category : Science
Languages : en
Pages : 366
Book Description
Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided by Dr. Huang and Dr. Le enable readers to become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications, and TensorFlow Hub. Each chapter has one corresponding Lab with step-by-step instruction to help the reader practice and accomplish a specific learning outcome. Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning. - Introduces readers to the usefulness of neural networks and Deep Learning methods - Provides readers with in-depth understanding of the architecture and operation of Deep Convolutional Neural Networks - Demonstrates the visualization needed for designing neural networks - Provides readers with an in-depth understanding of regression problems, binary classification problems, multi-category classification problems, Variational Auto-Encoder, Generative Adversarial Network, and Object detection
Publisher: Academic Press
ISBN: 0323901999
Category : Science
Languages : en
Pages : 366
Book Description
Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided by Dr. Huang and Dr. Le enable readers to become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications, and TensorFlow Hub. Each chapter has one corresponding Lab with step-by-step instruction to help the reader practice and accomplish a specific learning outcome. Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning. - Introduces readers to the usefulness of neural networks and Deep Learning methods - Provides readers with in-depth understanding of the architecture and operation of Deep Convolutional Neural Networks - Demonstrates the visualization needed for designing neural networks - Provides readers with an in-depth understanding of regression problems, binary classification problems, multi-category classification problems, Variational Auto-Encoder, Generative Adversarial Network, and Object detection
The National Laboratory System in the U.S., 1947-1962
Author: Peter James Westwick
Publisher:
ISBN:
Category : Laboratories
Languages : en
Pages : 444
Book Description
Publisher:
ISBN:
Category : Laboratories
Languages : en
Pages : 444
Book Description
Norfolk and Western Magazine
Author:
Publisher:
ISBN:
Category : Railroads
Languages : en
Pages : 1674
Book Description
Publisher:
ISBN:
Category : Railroads
Languages : en
Pages : 1674
Book Description