Author: Dale ShuttleworthPublisher: Routledge
ISBN: 1134915705
Category : Education
Languages : en
Pages : 322
Book Description
First Published in 2004. Routledge is an imprint of Taylor & Francis, an informa company.
Enterprise Learning in Action
Author: Dale ShuttleworthPublisher: Routledge
ISBN: 1134915705
Category : Education
Languages : en
Pages : 322
Book Description
First Published in 2004. Routledge is an imprint of Taylor & Francis, an informa company.
Enterprise Learning in Action
Author: Dale E. ShuttleworthPublisher:
ISBN:
Category : Business and education
Languages : en
Pages : 222
Book Description
Enterprise Learning in Action
Author: Dale ShuttleworthPublisher: Routledge
ISBN: 1134915713
Category : Education
Languages : en
Pages : 239
Book Description
Drawing on case studies in community and enterprise learning from around the world, Dale Shuttleworth shows how young people can be taught the enterprise skills which will enable them to survive in today's uncertain world.
Learning in Action
Author: David A. GarvinPublisher: Harvard Business Review Press
ISBN: 1633690393
Category : Business & Economics
Languages : en
Pages : 272
Book Description
Most managers today understand the value of building a learning organization. Their goal is to leverage knowledge and make it a key corporate asset, yet they remain uncertain about how best to get started. What they lack are guidelines and tools that transform abstract theory—the learning organization as an ideal—into hands-on implementation. For the first time in Learning in Action, David Garvin helps managers make the leap from theory to proven practice. Garvin argues that at the heart of organizational learning lies a set of processes that can be designed, deployed, and led. He starts by describing the basic steps in every learning process—acquiring, interpreting, and applying knowledge—then examines the critical challenges facing managers at each of these stages and the various ways the challenges can be met. Drawing on decades of scholarship and a wealth of examples from a wide range of fields, Garvin next introduces three modes of learning—intelligence gathering, experience, and experimentation—and shows how each mode is most effectively deployed. These approaches are brought to life in complete, richly detailed case studies of learning in action at organizations such as Xerox, L. L. Bean, the U. S. Army, and GE. The book concludes with a discussion of the leadership role that senior executives must play to make learning a day-to-day reality in their organizations.
Machine Learning Engineering in Action
Author: Ben WilsonPublisher: Simon and Schuster
ISBN: 1617298719
Category : Computers
Languages : en
Pages : 574
Book Description
Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you’ll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You’ll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You’ll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author’s extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer. Table of Contents PART 1 AN INTRODUCTION TO MACHINE LEARNING ENGINEERING 1 What is a machine learning engineer? 2 Your data science could use some engineering 3 Before you model: Planning and scoping a project 4 Before you model: Communication and logistics of projects 5 Experimentation in action: Planning and researching an ML project 6 Experimentation in action: Testing and evaluating a project 7 Experimentation in action: Moving from prototype to MVP 8 Experimentation in action: Finalizing an MVP with MLflow and runtime optimization PART 2 PREPARING FOR PRODUCTION: CREATING MAINTAINABLE ML 9 Modularity for ML: Writing testable and legible code 10 Standards of coding and creating maintainable ML code 11 Model measurement and why it’s so important 12 Holding on to your gains by watching for drift 13 ML development hubris PART 3 DEVELOPING PRODUCTION MACHINE LEARNING CODE 14 Writing production code 15 Quality and acceptance testing 16 Production infrastructure
Action Learning in Practice
Author: Mike PedlerPublisher: Routledge
ISBN: 1317185773
Category : Business & Economics
Languages : en
Pages : 480
Book Description
Previous editions of Action Learning in Practice established this authoritative overview of action learning around the world. Over the last decade the move towards action-based organizational learning and development has accelerated, and action learning is now an established part of the education and development mainstream in large and small organizations. Fully revised and updated, this fourth edition covers the origins of action learning with Reg Revans' ideas, and looks at their development and application today. Action learning is self-directed learning through tackling business and work problems with the support of peers and colleagues. A professional and diverse workforce, attracted, influenced and developed in this way is more able to deal effectively with the growing complexity and pressures of working life. As the limits of conventional training and development become more obvious, leaders are increasingly attracted to action-based approaches to learning when seeking better outcomes and returns on investment.
Self-Determined Learning
Author: Stewart HasePublisher: A&C Black
ISBN: 1441191488
Category : Education
Languages : en
Pages : 224
Book Description
Heutagogy, or self-determined learning, redefines how we understand learning and provides some exciting opportunities for educators. It is a novel approach to educational practice, drawing on familiar concepts such as constructivism, capability, andragogy and complexity theory. Heutagogy is also supported by a substantial and growing body of neuroscience research. Self-Determined Learning explores how heutagogy was derived, and what this approach to learning involves, drawing on recent research and practical applications. The editors draw together contributions from educators and practitioners in different fields, illustrating how the approach can been used and the benefits its use has produced. The subjects discussed include: the nature of learning, heutagogy in the classroom, flexible curriculum, assessment, e-learning, reflective learning, action learning and research, and heutagogy in professional practice settings.
Strategy in Action
Author: Rachel E. CurtisPublisher: Harvard Education Press
ISBN: 1612500463
Category : Education
Languages : en
Pages : 240
Book Description
How can we systemically improve the quality of classroom instruction and the learning and achievement of students? In an era when isolated examples of excellence are not good enough, we need systems that support improvement and excellence for all. This book describes how systems can effectively engage in this complex, challenging, and crucial work. The authors explore three core competencies of high-performing school systems: (1) understanding what the work is—a deep understanding of the core business of facilitating learning, a vision of what that looks like, and an awareness of where the system is in relation to that vision; (2) knowing how to do the work—a theory of action for improving instruction, a focus on key strategies, and effective alignment of resources; and (3) building the individual and organizational “habits of mind” that foster continuous improvement. Each chapter includes examples that illustrate key concepts in action, questions to spur self-assessment in key areas of competence, and tools and resources for building capacity at different levels and stages of development.
Modular Online Learning Design
Author: Amanda Nichols HessPublisher: American Library Association
ISBN: 0838948146
Category : Language Arts & Disciplines
Languages : en
Pages : 143
Book Description
Does your online instruction program sometimes feel like a constant scramble to keep pace with requests and deadlines? Modular design is the answer. Approaching projects, whether large and small, with an eye towards future uses will put you on the path to accomplishing broader, organizational goals. And by intentionally building documentation and structure into your process, you will create content that can easily be scaled, modified, adapted, and transformed to meet different learner needs. Hess, experienced in online instruction in both K-12 and academic libraries, shows you how, using project examples of various sizes to illustrate each chapter’s concepts. Her resource guides you through such topics as the eight components of modular online learning design; key considerations for choosing the design model that best fits your organization and project; techniques for connecting your online learning goals with institutional strategy; using the IDEA process to align OER content with your instructional needs; documenting your planning with checklists, scaffolds, and templates; ensuring equity of access with all content formats using the Accessibility Inventory Index; principles for scaling up, down, or laterally; three models for more meaningful and functional collaboration with internal or external partners; and formative testing as a foundation for ongoing evaluation and assessment.
Learning to See
Author: Mike RotherPublisher: Lean Enterprise Institute
ISBN: 0966784308
Category : Business & Economics
Languages : en
Pages : 115
Book Description
Lean production is the gold standard in production systems, but has proven famously difficult to implement in North America. Mass production relies on large inventories, uses "push" processes and struggles with long lead times. Moving towards a system that eliminates muda ("waste") caused by overproduction, while challenging, proves necessary for improved efficiency. Often overlooked, value stream mapping is the essential planning stage for any Lean transformation. In Mike Rother and John Shook's essential guide, you follow the value stream mapping undertaken for Acme Stamping, for its current and future state. Fully illustrated and well-organized, Learning to See is a must-see for the value stream manager.