Название: What Is DesignOps?
Автор: Dave Malouf
Издательство: O’Reilly Media, Inc.
Год: 2019
Язык: английский
Формат: pdf (conv), epub
Размер: 10.1 MB

Design is no longer a value-add that only some companies choose to afford. In today’s marketplace it’s a valuable strategic contributor for every organization. But getting the most value out of a design practice requires that these same organizations create an intentional operational practice—design operations (DesignOps). This comprehensive report provides an introduction to DesignOps along with practical patterns for using it within your organization.

Название: Programming: The Ultimate Guide on Learning Technology and applications
Автор: Tim Gosling
Издательство: Amazon.com Services LLC
Год: 2020
Страниц: 152
Язык: английский
Формат: pdf (conv), epub
Размер: 10.1 MB

Python is a perfect choice for beginner to make your focus on in order to jump into the field of machine learning and data science. It is a minimalistic and intuitive language with a full-featured library line (also called frameworks) which significantly reduces the time required to get your first results. Pуthоn іѕ used іn mаnу bіg companies ѕuсh аѕ Gооglе, Instagram, Dropbox, Rеddіt аnd many mоrе whісh means mоrе job ѕсореѕ іn Pуthоn. Duе to іnсrеаѕіng dеmаnd of Pуthоn programmers, ѕtudеntѕ аnd bеgіnnеrѕ іn industries аrе сhооѕіng Pуthоn аѕ thеіr соrе рrоgrаmmіng lаnguаgе.

Название: Decision Making Theories and Methods Based on Interval-Valued Intuitionistic Fuzzy Sets
Автор: Shuping Wan, Jiuying Dong
Издательство: Springer
Год: 2020
Страниц: 326
Язык: английский
Формат: pdf (true), epub
Размер: 23.9 MB

This is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations. Including numerous application examples and illustrations with tables and figures and presenting the authors’ latest research developments, it is a valuable resource for researchers and professionals in the fields of fuzzy mathematics, operations research, information science, management science and decision analysis.

Название: Accelerated Software Trace Analysis, Revised Edition, Part 1: Fundamentals and Basic Patterns
Автор: Dmitry Vostokov
Издательство: OpenTask
Год: 2019
Страниц: 110
Язык: английский
Формат: epub
Размер: 29.2 MB

This book is a revised edition of the original Accelerated Windows Software Trace Analysis training course. General trace and log analysis pattern language covers any execution artifact from a small debugging trace to a distributed log with billions of messages from hundreds of computers, thousands of software components, threads, and processes. It also allows the application of uniform diagnostics and anomaly detection across diverse software environments, troubleshooting and debugging Windows, Mac OS X, Linux, Android, iOS, and any other possible computer platform including networking and IoT. Part 1 covers fundamentals and explains more than 60 basic trace and log analysis patterns, which are now cross-referenced in this improved and less Windows-centric edition. It can also serve as a reference.

Название: Machine Learning with Python: Step by Step methods to master Machine Learning with Python
Автор: Alexander Cane
Издательство: Amazon.com Services LLC
Год: 2020
Формат: epub/mobi/azw3/pdf(conv.)
Страниц: 123
Размер: 10.6 Mb
Язык: English

Are you looking for a guide that will teach you all you need to know about machine learning? Are you looking for a way to learn how to write algorithms from scratch? Then read on…
Artificial intelligence is a common part of our lives, and we use it daily. Machine learning is one application of artificial intelligence and is where software, computers and devices use cognition to learn. If you use Siri on an iPhone, Cortana on your Windows PC, or Alexa, you are already making use of machine learning, especially when they provide you with traffic news, weather predictions, search results, and more.

Название: DATA SCIENCE FROM SCRATCH: Complete guide to master data process, mining, data-analytic, neural networks, machine learning in Python, Linear Algebra, Statistics, Coding, Applications Decision Tree
Автор: G.S. Collins
Издательство: Amazon.com Services LLC
Год: 2020
Формат: epub/pdf(conv.)
Страниц: 151
Размер: 10.4 Mb
Язык: English

Become the master of machine learning with this powerful guide.
Do you want to know more about neural networks? Have you heard of machine learning, but you’re not sure where to begin?
Written with the beginner in mind, this detailed guide breaks down everything you need to know about deep and machine learning in a simple, easy-to-understand way. Machine learning is a fascinating and ever-growing field, and its development will shape our futures. Now, you can understand what makes this topic so powerful no matter your level of experience.

Название: Rhetorical Code Studies : Discovering Arguments in and Around Code
Автор: Kevin Brock
Издательство: University of Michigan Press
Год: 2019
Страниц: 233
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Software developers work rhetorically to make meaning through the code they write. In some ways, writing code is like any other form of communication; in others, it proves to be new, exciting, and unique. In Rhetorical Code Studies, Kevin Brock explores how software code serves as meaningful communication through which software developers construct arguments that are made up of logical procedures and express both implicit and explicit claims as to how a given program operates.

Название: Industrial AI: Applications with Sustainable Performance
Автор: Jay Lee
Издательство: Springer
Год: 2020
Страниц: 176
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book introduces Industrial Artificial Intelligence (AI) in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals.

Название: Practical MATLAB Deep Learning: A Project-Based Approach
Автор: Michael Paluszek, Stephanie Thomas
Издательство: Apress
Год: 2020
Страниц: 260
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You’ll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images.

Название: Statistics, Data Mining and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data, Updated Ed
Автор: Željko Ivezić, Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray
Издательство: Princeton University Press
Год: 2020
Формат: PDF
Страниц: 560
Размер: 39,5 Mb
Язык: English

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book.