Black Book Vol 1 7 2020 Edition Read Free Pdf Access


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Operating Systems


Operating Systems

Author: Remzi H. Arpaci-Dusseau

language: en

Publisher: Createspace Independent Publishing Platform

Release Date: 2018-09


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"This book is organized around three concepts fundamental to OS construction: virtualization (of CPU and memory), concurrency (locks and condition variables), and persistence (disks, RAIDS, and file systems"--Back cover.

Interpretable Machine Learning


Interpretable Machine Learning

Author: Christoph Molnar

language: en

Publisher: Lulu.com

Release Date: 2020


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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.

Mathematics for Machine Learning


Mathematics for Machine Learning

Author: Marc Peter Deisenroth

language: en

Publisher: Cambridge University Press

Release Date: 2020-04-23


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Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.