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| Author | : Peter Adams |
| Publisher | : Bedford Books |
| Total Pages | : |
| Release | : 2019-12-13 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 9781319354268 |
| Author | : Peter Adams |
| Publisher | : |
| Total Pages | : |
| Release | : 2019-12-13 |
| Genre | : |
| ISBN | : 9781319354275 |
| Author | : Bedford/St.Martin's |
| Publisher | : Macmillan Higher Education |
| Total Pages | : 67 |
| Release | : 2019-12-02 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 131935081X |
Bedford/St. Martin’s is pleased to offer Documenting Sources in APA Style: 2020 Update. This brief 48-page print supplement adapts guidelines from the recently released Publication Manual of the American Psychological Association, 7th Edition, and can be packaged at no additional cost with any Bedford text. Students will appreciate the practical examples throughout; instructors will value the explanations designed to simplify citation practices. Contact your representative to learn more about packaging options.
| Author | : American Psychological Association |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2012 |
| Genre | : Authorship |
| ISBN | : 9781433805592 |
The Publication Manual of the American Psychological Association is the style manual of choice for writers, editors, students, and educators in the social and behavioral sciences. It provides invaluable guidance on all aspects of the writing process, from the ethics of authorship to the word choice that best reduces bias in language. Well-known for its authoritative and easy-to-use reference and citation system, the Publication Manual also offers guidance on choosing the headings, tables, figures, and tone that will result in strong, simple, and elegant scientific communication.
| Author | : American Psychological Association |
| Publisher | : American Psychological Association (APA) |
| Total Pages | : 428 |
| Release | : 2019-10 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 9781433832161 |
The Publication Manual of the American Psychological Association is the style manual of choice for writers, editors, students, and educators in the social and behavioral sciences, nursing, education, business, and related disciplines.
| Author | : American Nurses Association |
| Publisher | : Nursesbooks.org |
| Total Pages | : 42 |
| Release | : 2001 |
| Genre | : Business & Economics |
| ISBN | : 1558101764 |
Pamphlet is a succinct statement of the ethical obligations and duties of individuals who enter the nursing profession, the profession's nonnegotiable ethical standard, and an expression of nursing's own understanding of its commitment to society. Provides a framework for nurses to use in ethical analysis and decision-making.
| Author | : American Medical Association |
| Publisher | : |
| Total Pages | : 72 |
| Release | : 1919 |
| Genre | : Authorship |
| ISBN | : |
| Author | : Christoph Molnar |
| Publisher | : Lulu.com |
| Total Pages | : 320 |
| Release | : 2020 |
| Genre | : Artificial intelligence |
| ISBN | : 0244768528 |
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
| Author | : Andrew Collette |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 152 |
| Release | : 2013-10-21 |
| Genre | : Computers |
| ISBN | : 149194501X |
Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes. Through real-world examples and practical exercises, you’ll explore topics such as scientific datasets, hierarchically organized groups, user-defined metadata, and interoperable files. Examples are applicable for users of both Python 2 and Python 3. If you’re familiar with the basics of Python data analysis, this is an ideal introduction to HDF5. Get set up with HDF5 tools and create your first HDF5 file Work with datasets by learning the HDF5 Dataset object Understand advanced features like dataset chunking and compression Learn how to work with HDF5’s hierarchical structure, using groups Create self-describing files by adding metadata with HDF5 attributes Take advantage of HDF5’s type system to create interoperable files Express relationships among data with references, named types, and dimension scales Discover how Python mechanisms for writing parallel code interact with HDF5
| Author | : Steven L. Brunton |
| Publisher | : Cambridge University Press |
| Total Pages | : 615 |
| Release | : 2022-05-05 |
| Genre | : Computers |
| ISBN | : 1009098489 |
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
