Название: jаvascript: Programmieren für Einsteiger: Der leichte Weg zum jаvascript-Experten
Автор: Paul Fuchs
Издательство: BMU Verlag
Год: 2019
Формат: PDF
Страниц: 393
Размер: 10 Mb
Язык: Deutsch

Der leichte Weg zum jаvascript-Experten!jаvascript ist die wichtigste clientseitige Programmiersprache zur Erstellung moderner dynamischer Webseiten, und zudem überaus einfach zu erlernen.

Название: Declarative Logic Programming: Theory, Systems, and Applications
Автор: Michael Kifer, Yanhong Annie Liu
Издательство: ACM Books
Год: 2018
Страниц: 615
Язык: английский
Формат: pdf (true), epub
Размер: 28.1 MB

Logic Programming (LP) is at the nexus of Knowledge Representation, Artificial Intelligence, Mathematical Logic, Databases, and Programming Languages. It is fascinating and intellectually stimulating due to the fundamental interplay among theory, systems, and applications brought about by logic. Logic programs are more declarative in the sense that they strive to be logical specifications of "what" to do rather than "how" to do it, and thus they are high-level and easier to understand and maintain. Yet, without being given an actual algorithm, LP systems implement the logical specifications automatically.

Название: Programming: 6 book in 1: Arduino Programming for Beginners; jаvascript for Beginners; Linux for Beginners; SQL for Beginners; Python Programming for Beginners; Python for Data Science
Автор: Matthew Python, Matthew Arduino
Издательство: Amazon.com Services LLC
Год: 2020
Формат: epub/pdf(conv.)
Страниц: 828
Размер 10 Mb
Язык: English

“Programming: 6 Books in 1: Arduino Programming for Beginners; jаvascript for Beginners; Linux for Beginners; SQL for Beginners; Python Programming for Beginners; Python for Data Science” by Matthew Python and Matthew Arduino.

Название: OOP Concepts Booster : Take Your Coding Skills to the Next Level
Автор: Rakesh Singh
Издательство: Notion Press
Год: 2019
Формат: pdf(conv.)
Страниц: 174
Размер: 1 Mb
Язык: English

It’s time to level up your programming skills!
The one thing that giants like Apple, Microsoft and Facebook have in common is that they became tech powerhouses by following a simple principle; they constantly capitalize on innovative concepts. If you want to create revolutionary software as they have, then you need to follow in their footsteps. That first step starts with mastering Object-Oriented Programming concepts!

Название: Оформление программного кода. 2-е изд.
Автор: Столяров А.В.
Издательство: МАКС Пресс
Год: 2019
Страниц: 118
Язык: русский
Формат: pdf, djvu
Размер: 20.9 MB

В пособии изложены основные принципы, применяющиеся для повышения читаемости текстов компьютерных программ и их доступности для анализа человеком; в частности, даются рекомендации по разбиению программ на модули и подсистемы, уделяется много внимания различным стилям расстановки структурных отступов и незначащих (декоративных) пробелов.

Название: Программирование. Введение в профессию. Том IV. Парадигмы
Автор(ы): Столяров А.В.
Издательство: М.: МАКС Пресс
Год: 2020
Страниц: 658
Формат: PDF
Размер: 10 Мб
Язык: русский

Четвертый, заключительный том учебника «Программирование: введение в профессию» посвящен многообразию парадигм программирования; в нем рассматривается язык Си++, абстрактные типы данных и объектно-ориентированное программирование; описаны такие языки, как Лисп, Scheme, Пролог и Хоуп, функциональное программирование, ленивые вычисления; в качестве иллюстрации командно-скриптового подхода рассмотрен язык Tcl. Обсуждается дихотомия Оустерхаута, а также компиляция и интерпретация как парадигмы особого рода.

Название: Deep Learning for Time Series Forecasting: Predict the Future with MLPs, CNNs and LSTMs in Python
Автор: Jason Brownlee
Издательство: Machine Learning Mastery Pty. Ltd.
Год: 2018
Формат: True PDF
Страниц: 574
Размер: 13.9 Mb
Язык: English

Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.

Название: Graphic Python Algorithms: Data Structure and Algorithms for python
Автор: Yang Hu
Издательство: Amazon.com Services LLC
Год: 2020
Формат: epub
Страниц: 250
Размер: 33 Mb
Язык: English

Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key cryptography and database system implementation. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews.
The book covers a broad range of algorithms , yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study.

Название: Heterogeneous Computing: Hardware and Software Perspectives
Автор: Mohamed Zahran
Издательство: Association for Computing Machinery
Год: 2019
Формат: true pdf/epub
Страниц: 130
Размер: 10 Mb
Язык: English

If you look around you will find that all computer systems, from your portable devices to the strongest supercomputers, are heterogeneous in nature. The most obvious heterogeneity is the existence of computing nodes of different capabilities (e.g. multicore, GPUs, FPGAs, ...). But there are also other heterogeneity factors that exist in computing systems, like the memory system components, interconnection, etc. The main reason for these different types of heterogeneity is to have good performance with power efficiency.

Название: Big Data Analytics for Cyber-Physical Systems: Machine Learning for the Internet of Things
Автор: Guido Dartmann (Editor), Houbing Song (Editor), Anke Schmeink (Editor)
Издательство: Elsevier
Год: 2019
Формат: True PDF
Страниц: 396
Размер: 37.4 Mb
Язык: English

Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, IoT gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interaction between IoT technology and the mathematical tools used to evaluate the extracted data of those systems. Each chapter provides the reader with a broad list of data analytics and machine learning methods for multiple IoT applications. Additionally, this volume addresses the educational transfer needed to incorporate these technologies into our society by examining new platforms for IoT in schools, new courses and concepts for universities and adult education on IoT and data science.