Delmar's Clinical Medical Assisting-Iml 3e
Delmar's Clinical Medical Assisting-Iml 3e

Author: Lindh

Publisher:

Published: 2005-12

Total Pages: 584

ISBN-13: 9781401881344

DOWNLOAD EBOOK

Includes Transition Guide from the 2nd edition to the 3rd edition; Answer Key to Text Review Questions and Critical Thinking Questions; Answers to Workbook Exercises, Activities, and Case Study Questions

Purification of Laboratory Chemicals
Purification of Laboratory Chemicals

Author: W.L.F. Armarego

Publisher: Elsevier

Published: 2003-03-07

Total Pages: 627

ISBN-13: 0080515460

DOWNLOAD EBOOK

Now in its fifth edition, the book has been updated to include more detailed descriptions of new or more commonly used techniques since the last edition as well as remove those that are no longer used, procedures which have been developed recently, ionization constants (pKa values) and also more detail about the trivial names of compounds.In addition to having two general chapters on purification procedures, this book provides details of the physical properties and purification procedures, taken from literature, of a very extensive number of organic, inorganic and biochemical compounds which are commercially available. This is the only complete source that covers the purification of laboratory chemicals that are commercially available in this manner and format.* Complete update of this valuable, well-known reference* Provides purification procedures of commercially available chemicals and biochemicals* Includes an extremely useful compilation of ionisation constants

Index Medicus
Index Medicus

Author:

Publisher:

Published: 2004

Total Pages: 1938

ISBN-13:

DOWNLOAD EBOOK

Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.

Interpretable Machine Learning
Interpretable Machine Learning

Author: Christoph Molnar

Publisher: Lulu.com

Published: 2020

Total Pages: 320

ISBN-13: 0244768528

DOWNLOAD EBOOK

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.