Intelligence Learning And Action
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Intelligence Learning And Action
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Author : Richard R. Skemp
language : en
Publisher: Chichester [Eng.] ; New York : Wiley
Release Date : 1979
Intelligence Learning And Action written by Richard R. Skemp and has been published by Chichester [Eng.] ; New York : Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Education categories.
Intelligence Learning And Action
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Author : Richard R. Skemp
language : en
Publisher: Chichester [Eng.] ; New York : Wiley
Release Date : 1979
Intelligence Learning And Action written by Richard R. Skemp and has been published by Chichester [Eng.] ; New York : Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Education categories.
Collective Intelligence In Action
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Author : Satnam Alag
language : en
Publisher: Manning Publications
Release Date : 2008
Collective Intelligence In Action written by Satnam Alag and has been published by Manning Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Provides information on using a Java-based CI toolkit to mine information to build more effective Web sites.
Systems Thinking
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Author : Piero Mella
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-06-07
Systems Thinking written by Piero Mella and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-07 with Business & Economics categories.
The core belief underlying this book is that the most useful and effective models to strengthen our intelligence are system ones, developed following the logic of Systems Thinking. Such models can explore complexity, dynamics, and change, and it is the author’s view that intelligence depends on the ability to construct models of this nature. The book is designed to allow the reader not only to acquire simple information on Systems Thinking but above all to gradually learn the logic and techniques that make this way of thinking an instrument for the improvement of intelligence. In order to aid the learning and practice of the Systems Thinking discipline, the author has abandoned a rigid formal language for a more discursive style. He writes in the first person, with an ample number of citations and critical analyses, and without ever giving in to the temptation to use formal mathematics.
Learning In Action
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Author : David A. Garvin
language : en
Publisher: Harvard Business Review Press
Release Date : 2003-03-25
Learning In Action written by David A. Garvin and has been published by Harvard Business Review Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-03-25 with Business & Economics categories.
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 In Action
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Author : Peter Harrington
language : en
Publisher: Manning
Release Date : 2012-04-19
Machine Learning In Action written by Peter Harrington and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-19 with Computers categories.
Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside A no-nonsense introduction Examples showing common ML tasks Everyday data analysis Implementing classic algorithms like Apriori and Adaboos Table of Contents PART 1 CLASSIFICATION Machine learning basics Classifying with k-Nearest Neighbors Splitting datasets one feature at a time: decision trees Classifying with probability theory: naïve Bayes Logistic regression Support vector machines Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION Predicting numeric values: regression Tree-based regression PART 3 UNSUPERVISED LEARNING Grouping unlabeled items using k-means clustering Association analysis with the Apriori algorithm Efficiently finding frequent itemsets with FP-growth PART 4 ADDITIONAL TOOLS Using principal component analysis to simplify data Simplifying data with the singular value decomposition Big data and MapReduce
Emotional Intelligence In Action
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Author : Marcia Hughes
language : en
Publisher: John Wiley & Sons
Release Date : 2011-02-23
Emotional Intelligence In Action written by Marcia Hughes and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-23 with Business & Economics categories.
Emotional Intelligence in Action shows how to tap the power of EI through forty-six exercises that can be used to build effective emotional skills and create real change. The workouts are designed to align with the four leading emotional intelligence measures—EQ-I or EQ-360, ECI 360, MSCEIT, and EQ Map, —or can be used independently or as part of a wider leadership and management development program. All of the book's forty-six exercises offer experiential learning scenarios that have been proven to enhance emotional intelligence competencies.
Intelligence Its Structure Growth And Action
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Author : R.B. Cattell
language : en
Publisher: Elsevier
Release Date : 1987-07-01
Intelligence Its Structure Growth And Action written by R.B. Cattell and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-07-01 with Psychology categories.
With essentially the same basis as the 1971 Abilities, Their Structure, Growth and Action, this new volume reflects the developments of subsequent years.
Machine Learning Engineering In Action
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Author : Ben Wilson
language : en
Publisher: Simon and Schuster
Release Date : 2022-05-17
Machine Learning Engineering In Action written by Ben Wilson and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-17 with Computers categories.
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. 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.
Intelligent Systems And Applications
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Author : Kohei Arai
language : en
Publisher: Springer Nature
Release Date : 2020-08-25
Intelligent Systems And Applications written by Kohei Arai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-25 with Technology & Engineering categories.
The book Intelligent Systems and Applications - Proceedings of the 2020 Intelligent Systems Conference is a remarkable collection of chapters covering a wider range of topics in areas of intelligent systems and artificial intelligence and their applications to the real world. The Conference attracted a total of 545 submissions from many academic pioneering researchers, scientists, industrial engineers, students from all around the world. These submissions underwent a double-blind peer review process. Of those 545 submissions, 177 submissions have been selected to be included in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have enabled a larger number of problems to be tackled more effectively.This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for such an international conference which serves as a venue to report on up-to-the-minute innovations and developments. This book collects both theory and application based chapters on all aspects of artificial intelligence, from classical to intelligent scope. We hope that readers find the volume interesting and valuable; it provides the state of the art intelligent methods and techniques for solving real world problems along with a vision of the future research.