Название: Computational Methods for Engineers: Modeling, Algorithms and Analysis
Автор: J.P. Mmbaga, K. Nandakumar, R.E. Hayes, M.R. Flynn
Издательство: ALPHA Education Press
Год: 2021
Формат: PDF
Страниц: 335
Размер: 10.43 MB
Язык: English

Revolutionary advances in hardware and software technology have made computer aided design and analysis a standard tool in engineering practice. This obviously puts a lot of power in the hands of the end user, in order to use these tools wisely and interpret the results correctly, users are expected to have a sound knowledge of the relationship between the physical world and the mathematical model and that between the mathematical model and the numerical approximation.

Название: A Logical Theory of Causality
Автор: Alexander Bochman
Издательство: The MIT Press
Год: 2021
Страниц: 366
Язык: английский
Формат: epub
Размер: 10.1 MB

A general formal theory of causal reasoning as a logical study of causal models, reasoning, and inference. In this book, Alexander Bochman presents a general formal theory of causal reasoning as a logical study of causal models, reasoning, and inference, basing it on a supposition that causal reasoning is not a competitor of logical reasoning but its complement for situations lacking logically sufficient data or knowledge. Bochman also explores the relationship of this theory with the popular structural equation approach to causality proposed by Judea Pearl and explores several applications ranging from artificial intelligence to legal theory, including abduction, counterfactuals, actual and proximate causality, dynamic causal models, and reasoning about action and change in Artificial Intelligence (AI).

Название: Machine Learning, revised and updated edition
Автор: Ethem Alpaydin
Издательство: The MIT Press
Год: 2021
Формат: ePUB, PDF
Страниц: 280
Размер: 10 Mb
Язык: English

A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars.
Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use everyday, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydín offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.

Название: Technical Debt in Practice: How to Find It and Fix It
Автор: Neil Ernst, Rick Kazman, Julien Delange
Издательство: The MIT Press
Год: 2021
Страниц: 288
Язык: английский
Формат: True EPUB
Размер: 12.8 MB

The practical implications of technical debt for the entire software lifecycle; with examples and case studies. Technical debt in software is incurred when developers take shortcuts and make ill-advised technical decisions in the initial phases of a project, only to be confronted with the need for costly and labor-intensive workarounds later. This book offers advice on how to avoid technical debt, how to locate its sources, and how to remove it. It focuses on the practical implications of technical debt for the entire software life cycle, with examples and case studies from companies that range from Boeing to Twitter. Technical debt is normal; it is part of most iterative development processes. But if debt is ignored, over time it may become unmanageably complex, requiring developers to spend all of their effort fixing bugs, with no time to add new features--and after all, new features are what customers really value.

Название: Deep Learning-Based Face Analytics
Автор: Nalini K. Ratha, Vishal M. Patel, Rama Chellappa
Издательство: Springer
Год: 2021
Формат: PDF
Страниц: 405
Размер: 15,3 Mb
Язык: English

This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field.

Название: Hacking Kubernetes: Threat-Driven Analysis and Defense (Third Early Release)
Автор: Andrew Martin, Michael Hausenblas
Издательство: O’Reilly Media, Inc.
Год: 2021-08-16
Страниц: 132
Язык: английский
Формат: epub
Размер: 12.4 MB

Running cloud native workloads on Kubernetes can be challenging: keeping them secure is even more so. Kubernetes' complexity offers malicious in-house users and external attackers alike a large assortment of attack vectors. Hacking Kubernetes reviews defaults and threat models and shows how to protect against attacks. Securing your workloads is both essential and urgent, so this invaluable hands-on guide is available to you in this early release edition before it's available to the general public.

Название: An Introduction to Lifted Probabilistic Inference
Автор: Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan
Издательство: The MIT Press
Серия: Neural Information Processing
Год: 2021
Страниц: 630
Язык: английский
Формат: epub
Размер: 15.9 MB

Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models. Statistical relational Artificial Intelligence (StaRAI) studies the integration of reasoning under uncertainty with reasoning about individuals and relations. The representations used are often called relational probabilistic models. Lifted inference is about how to exploit the structure inherent in relational probabilistic models, either in the way they are expressed or by extracting structure from observations. This book covers recent significant advances in the area of lifted inference, providing a unifying introduction to this very active field.

Название: Statistical Quality Control: Using MINITAB, R, JMP and Python
Автор: Gupta, Bhisham C.
Издательство: Wiley
Год: 2021
Формат: True PDF
Страниц: 393
Размер: 10 Mb
Язык: English

This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept.

Название: C# Programming for Absolute Beginners: Learn to Think Like a Programmer and Start Writing Code
Автор: Radek Vystavel
Издательство: Apress
Год: 2021
Формат: PDF
Страниц: 376
Размер: 11,7 Mb
Язык: English

Get started using the C# programming language. Based on the author’s 15 years of experience teaching beginners, this book provides you with a step-by-step introduction to the principles of programming, or rather, how to think like a programmer. The task-solution approach will get you immersed, with minimum theory and maximum action.

Название: Advanced Reactor Modelling with MATLAB: Case Studies with Solved Examples
Автор: Riccardo Tesser, Vincenzo Russo
Издательство: De Gruyter
Год: 2021
Формат: PDF
Страниц: 300
Размер: 35 Mb
Язык: English

Offers the reader a modern approach to reactor description and modelling. Using the widely applied numerical language MATLAB, it provides the reader with categorized groups of general code for a wide variety of chemical reactors. Being designed as a tool for researchers and professionals, the code can easily be extended and adapted by the reader to their own specific problems.