Andrew's just trying to get through school photo day with one aim: a photo of him which his mum will like. But today of all days, the world seems out to get him. There's a bully, the science experiment gone wrong, scary news about his grandmother, and someone else's juice snot (don't ask).Andrew struggles with anxiety, and the little kernel of worry in his stomach is getting hotter and hotter . . .Can he make it through the day without popping? A heartfelt and laugh-out-loud-funny story about letting go of control and accepting help, interspersed with Rob Harrell's amazing spot art and comic panels that depict the real, difficult feelings of anxiety and OCD, as well as real tips for coping.
Sayyid Muhammad Husayn Tabataba'i (1901-1982) was a prominent Sufi Muslim scholar and seminarian. Based upon a series of lectures delivered in 1949 and 1950, this text presents reflections on his pers
"The Innermost Kernel" offers an insightful examination of the research and history of the physicist and Nobel Laureate Wolfgang Pauli and his interest in Jungian psychology, philosophy and western wo
Describes the process of corn production, including planting the kernels, tending and harvesting the crop, and transporting the corn to the grocery store so that it may be bought and eaten.
Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book
An all-new Popcorn Shop Mystery bursts on the scene, featuring gourmet popcorn entrepreneur Rebecca Anderson and her poodle Sprocket.Opening a gourmet popcorn shop was never on Rebecca Anderson’s buck
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel funct
This volume is a superb introduction to the richness and originality of Abraham and Torok's approach to psychoanalysis and their psychoanalytic approach to literature. Abraham and Torok advocate a fo
This volume is a superb introduction to the richness and originality of Abraham and Torok's approach to psychoanalysis and their psychoanalytic approach to literature. Abraham and Torok advocate a for
In order to thoroughly understand what makes Linux tick and why it works so well on a wide variety of systems, you need to delve deep into the heart of the kernel. The kernel handles all interactions
Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent yearsThis book covers kernel analysis topics ranging from the fundamental theo
The Support Vector Machine is a powerful new learning algorithm for solving a variety of learning and function estimation problems, such as pattern recognition, regression estimation, and operator inv
Find an introduction to the architecture, concepts and algorithms of the Linux kernel in Professional Linux Kernel Architecture, a guide to the kernel sources and large number of connections among subsystems. Find an introduction to the relevant structures and functions exported by the kernel to userland, understand the theoretical and conceptual aspects of the Linux kernel and Unix derivatives, and gain a deeper understanding of the kernel. Learn how to reduce the vast amount of information contained in the kernel sources and obtain the skills necessary to understand the kernel sources.
Linux Kernel Development details the design and implementation of the Linux kernel, presenting the content in a manner that is beneficial to those writing and developing kernel code, as well as to pro
Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate student
