Free Download Linkedin – Advanced Linux The Linux Kernel (2024)

Released: 12/2024
Duration: 2h 51m | .MP4 1280×720, 30 fps(r) | AAC, 48000 Hz, 2ch | 341 MB
Level: Advanced | Genre: eLearning | Language: English
Upskill as a Linux developer, network engineer, or DevOps professional. In this hands-on course, instructor Kevin Dankwardt provides an

Overview

of the role and functionality of the Linux kernel, including setup and how to write, compile, and insert loadable kernel modules. Along the way, find out why configuring and building custom kernels can help to illuminate the kernel’s breadth of functionality as well as provide insights on the kernel’s capabilities.

Free Download Kaiwan N Billimoria, "Linux Kernel Debugging: Leverage proven tools and advanced techniques to effectively debug Linux kernels and kernel modules"
English | 2022 | ISBN: 1801075034 | PDF | pages: 639 | 24.6 mb
Effectively debug kernel modules, device drivers, and the kernel itself by gaining a solid understanding of powerful open source tools and advanced kernel debugging techniques

Free Download Generalized Kernel Equating with Applications in R
English | 2025 | ISBN: 1138196983 | 272 Pages | PDF EPUB (True) | 6 MB
Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the necessary tools and methodologies for accurate and fair score comparisons.

Free Download Heat Kernel on Lie Groups and Maximally Symmetric Spaces (Frontiers in Mathematics) by Ivan G. Avramidi
English | April 26, 2023 | ISBN: 3031274504 | 212 pages | MOBI | 27 Mb
This monograph studies the heat kernel for the spin-tensor Laplacians on Lie groups and maximally symmetric spaces. It introduces many original ideas, methods, and tools developed by the author and provides a list of all known exact results in explicit form – and derives them – for the heat kernel on spheres and hyperbolic spaces. Part I considers the geometry of simple Lie groups and maximally symmetric spaces in detail, and Part II discusses the calculation of the heat kernel for scalar, spinor, and generic Laplacians on spheres and hyperbolic spaces in various dimensions. This text will be a valuable resource for researchers and graduate students working in various areas of mathematics – such as global analysis, spectral geometry, stochastic processes, and financial mathematics – as well in areas of mathematical and theoretical physics – including quantum field theory, quantum gravity, string theory, and statistical physics.

Free Download Semantic Kernel C#
Published 9/2024
Created by Stipe Cule
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 13 Lectures ( 1h 17m ) | Size: 586 MB

Free Download Introduction to Linux Kernel Development
Published 9/2024
Created by Chandrashekar Babu
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 31 Lectures ( 27h 24m ) | Size: 22.2 GB

Free Download Linux Kernel Programming – Second Edition: A comprehensive and practical guide to kernel internals, writing modules, and kernel synchronization by Kaiwan N Billimoria
English | February 29, 2024 | ISBN: 1803232226 | 826 pages | EPUB | 48 Mb
Gain both a firm practical understanding and sufficient theoretical insight into the inner workings of Linux kernel internals, learn to write high-quality kernel module code, understand the complexities of kernel synchronization

Free Download Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines: Theory, Algorithms and Applications (Industrial and Applied Mathematics) by Jamal Amani Rad, Kourosh Parand, Snehashish Chakraverty
English | March 19, 2023 | ISBN: 9811965528 | 319 pages | MOBI | 38 Mb
This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is on orthogonal kernel functions, and the properties of the classical kernel functions-Chebyshev, Legendre, Gegenbauer, and Jacobi-are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations.

Free Download Conquering the Kernel: Dive into OS Development with Rust by Tony J. Johnson
English | May 30, 2024 | ISBN: N/A | ASIN: B0D5RJRSMP | 142 pages | EPUB | 6.60 Mb
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Free Download The Pre-Kernel as a Tractable Solution for Cooperative Games: An Exercise in Algorithmic Game Theory By Holger Ingmar Meinhardt (auth.)
2014 | 242 Pages | ISBN: 3642395481 | PDF | 3 MB
This present book provides an alternative approach to study the pre-kernel solution of transferable utility games based on a generalized conjugation theory from convex analysis. Although the pre-kernel solution possesses an appealing axiomatic foundation that lets one consider this solution concept as a standard of fairness, the pre-kernel and its related solutions are regarded as obscure and too technically complex to be treated as a real alternative to the Shapley value. Comprehensible and efficient computability is widely regarded as a desirable feature to qualify a solution concept apart from its axiomatic foundation as a standard of fairness. We review and then improve an approach to compute the pre-kernel of a cooperative game by the indirect function. The indirect function is known as the Fenchel-Moreau conjugation of the characteristic function. Extending the approach with the indirect function, we are able to characterize the pre-kernel of the grand coalition simply by the solution sets of a family of quadratic objective functions.