CIMA E2 Managing Performance

CIMA E2 Managing Performance

Author: BPP LEARNING MEDIA.

Publisher:

Published: 2023-10-14

Total Pages: 0

ISBN-13: 9781035508556

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BPP Learning Media provides comprehensive materials that highlight the areas to focus on for your exams and complement the syllabus to increase your understanding.


CIMA P2 Advanced Management Accounting

CIMA P2 Advanced Management Accounting

Author: BPP Learning Media

Publisher: BPP Learning Media

Published: 2016-11-15

Total Pages: 121

ISBN-13: 1509707409

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BPP Learning Media provides comprehensive materials that highlight the areas to focus on for your exams and complement the syllabus to increase your understanding.


CIMA E1 Managing Finance in a Digital World

CIMA E1 Managing Finance in a Digital World

Author: BPP LEARNING MEDIA.

Publisher:

Published: 2023-10-14

Total Pages: 0

ISBN-13: 9781035508549

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BPP Learning Media provides comprehensive materials that highlight the areas to focus on for your exams and complement the syllabus to increase your understanding.


ADKAR

ADKAR

Author: Jeff Hiatt

Publisher: Prosci

Published: 2006

Total Pages: 164

ISBN-13: 9781930885509

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In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change.


Mathematics for Machine Learning

Mathematics for Machine Learning

Author: Marc Peter Deisenroth

Publisher: Cambridge University Press

Published: 2020-04-23

Total Pages: 392

ISBN-13: 1108569323

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The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.


Site Reliability Engineering

Site Reliability Engineering

Author: Niall Richard Murphy

Publisher: "O'Reilly Media, Inc."

Published: 2016-03-23

Total Pages: 552

ISBN-13: 1491951176

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The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use


Introduction to Applied Linear Algebra

Introduction to Applied Linear Algebra

Author: Stephen Boyd

Publisher: Cambridge University Press

Published: 2018-06-07

Total Pages: 477

ISBN-13: 1316518965

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A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.