Название: Основы разработки программного обеспечения бортового радиоэлектронного оборудования летательных аппаратов. Учебное пособие. Практикум
Автор: Е. С. Земляный
Издательство: Знание-М
Год: 2024
Формат: Pdf
Страниц: 47, 56
Размер: 36,01 Мб
Язык: русский

Учебное пособие разработано на основании Федерального государственного образовательного стандарта Высшего образования – специалитет по специальности 24.05.06 «Системы управления летательных аппаратов» с учётом его профиля и может быть использовано для всех специализаций программы специалитета, перечисленных в указанном выше стандарте.

Название: Deep Learning with TensorFlow and Keras
Автор: Pratap Dangeti
Издательство: Wiley
Год: 2020
Страниц: 339
Язык: английский
Формат: epub
Размер: 11.8 MB

Truly a must have guide for every Data Science professional and deep learning enthusiast, the Wiley Deep Learning with Keras and TensorFlow brings together industry best practices, detailed code descriptions with simplified explanations and solved real life problems, to help any beginner to learn and master the techniques of Deep learning and coding in Keras and TensorFlow. TensorFlow has been chosen to help developers implement models in production environments and Keras for quickly prototyping new ideas in research scenarios. The book also includes best practices to improve the effectiveness in terms of tuning the models, handling memory constraints and usage of logs to save intermediate outputs. Finally, it concludes with the introduction to deep reinforcement learning for solving advanced problems in the field of AI and Artificial General Intelligence.

Название: Introduction to Data Science Practical Approach with R and Python
Автор: B. Uma Maheswari, R. Sujatha
Издательство: Wiley
Год: 2021
Страниц: 772
Язык: английский
Формат: epub
Размер: 11.3 MB

Introduction to Data Science: Practical Approach with R and Python covers all the fundamental concepts of Data Science in a concise manner. It offers a mix of insights and golden rules which would be needed in analyzing data. This book serves as a practical guide for Science/Engineering/MBA students – both at the undergraduate and postgraduate level interested in Data Science domain. As this domain evolves, the demand for data scientists and analysts is growing exponentially across the world. Educational institutions are integrating Data Science in their curriculum and aligning their programs to keep pace with the market requirements. This book is written to cater to the growing needs of the industry and academia. This book deals with the concepts of Data Science through the two most common open-source platforms applicable in the industry — R and Python. This book presents coding in a highly simplified manner, with step-by-step, clear instructions enhanced by visual aids of the output, making coding appear not so technical.

Название: Python for Data Science
Автор: Mohd. Abdul Hameed
Издательство: Wiley
Год: 2021
Страниц: 356
Язык: английский
Формат: epub
Размер: 10.1 MB

Python for Data Science contains the basic and advanced concepts to understand Python language. Besides, it furnishes the detailed procedure on how to implement a Data Science project. This book is intended to develop in readers the skills to independently work on their Data Science projects. In addition to UG, PG, and PhD students, this book would be a ready reckoner to IT professionals. Data Science is an emerging field, and its concepts can be applied to data from any domain. It is for this reason that many computer science professionals are desirous of shifting to the domain of Data Science. The contents of this book will aid aspirants to upgrade their knowledge of the programming language Python and help them switch to the field of Data Science.

Название: Concepts and Techniques of Programming in C
Автор: Dhabal Prasad Sethi, Manoranjan Pradhan
Издательство: I.K. International Pvt. Ltd./Dreamtech Press
Год: 2020
Страниц: 419
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The C programming language is one of the most widely offered courses in the undergraduate programmes (all branches of BTech, BSc Computer Science, and BCA) as well as various postgraduate programmes (MCA, MSc Computer Science and others). Apart from students, the book will also be useful for aspirants of various competitive examinations and budding programmers. The book is straightforward and simple in its approach, deals with fundamentals of computer, algorithms and flowcharts, error handling, different data types, variables, operators, input/output operations, decision statements, looping, unconditional statements, functions, arrays, strings, pointers, dynamic memory management, structure and union, file and file handling, and preprocessor directives.

Название: Statistics with Rust, Second Edition: Explore rust programming and its powerful crates across data science, machine learning and NLP projects
Автор: Keiko Nakamura
Издательство: GitforGits
Год: November 12, 2024
Страниц: 213
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

"Statistics with Rust, Second Edition" is designed to help you learn quickly, focusing on practical statistics using Rust scripts. The book is for readers who know the basics of statistics and Machine Learning. It gives quick explanations so you can try out concepts with hands-on coding. The book uses the newest version of Rust, 1.72.0, to help users build and secure statistical and machine learning algorithms. Each chapter is full of useful programs and code examples that will walk you through tasks like data manipulation, statistical tests, regression analysis, building machine learning models, and natural language processing. This second edition brings all chapters up to date with the latest in stats and Rust programming. It focuses on how you can put these things to practical use, with a detailed look at advanced algorithms like PCA, SVM, neural networks, and ensemble methods. This book is perfect for every data user, including data scientist, NLP engineers, Rust programmers, data engineers, data analysts and all those who are knowning simple basics of statistics and eager to use Rust programming for Data Science and Machine Learning projects.

Название: Fundamentals of Computing and Programming
Автор: S. Karthik, B. Chellaprabha, T. Kalaikumaran
Издательство: I.K. International Pvt. Ltd./Dreamtech Press
Год: 2019
Страниц: 201
Язык: английский
Формат: pdf (true)
Размер: 33.5 MB

Fundamentals of Computing and Programming provides not only theoretical knowledge but also practical aspects to make the student industry-ready. Each chapter is presented in a unique way with lot of examples, sample programs and most importantly comprehensive interview readiness questions in the last section, which will not only help revisit the concepts, but also make sure that the student can face the interviewer in this prescribed area without fear and hesitation. The book deals with topics like the fundamentals, generations, organization and architecture of computers in the beginning and then the chapter further deals with number systems, software classification, the Internet, C programming, fundamental rules and guidelines, operators, arrays and string operations the structures and unions and so on.

Название: Основы математического моделирования и оптимизации на языке Python
Автор: П. Головинский, А. Дробышев, Е. Михин
Издательство: Знание-М
Год: 2023
Формат: Pdf
Страниц: 109
Размер: 42,03 Мб
Язык: русский

В пособии представлены основные методы применения языка Python для решения задач моделирования, оптимизации и обработки данных. Каждая рассмотренная тема включает краткие теоретические сведения, подробный разбор практической работы, индивидуальные варианты заданий и контрольные вопросы по теме.

Название: Java 17 Backend Development: Design backend systems using Spring Boot, Docker, Kafka, Eureka, Redis, and Tomcat
Автор: Elara Drevyn
Издательство: GitforGits
Год: December 10, 2024
Страниц: 182
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

This book offers beginners and backend developers with practical guidance on developing robust server-side applications with Java 17. Each chapter is structured around hands-on examples, real-world challenges, and step-by-step solutions tailored to Java professionals aiming to elevate their expertise in backend systems. It seamlessly transitions through essential development phases, covering foundational elements like from object-oriented design and basic REST endpoints to advanced microservices architecture and container orchestration. It covers from wiring up databases with Hibernate to managing asynchronous communication with Apache Kafka and securing endpoints with Spring Security. You will explore caching strategies with Redis and diving into techniques to boost performance and reduce database load. The book also covers testing and debugging topics, highlighting modern tools and practices such as JUnit, Mockito, integration tests, and distributed tracing. This book is for Java developers, Spring developers, Spring Boot Programmers, web developers, and full-stack developers, as well as anyone interested in exploring the world of Java to improve the back-end of enterprise applications. You'll need some hands-on experience with Java 17 to get the most out of this book.

Название: Practical C++ Machine Learning: Hands-on strategies for developing simple machine learning models using C++ data structures and libraries
Автор: Anais Sutherland
Издательство: GitforGits
Год: November 8, 2024
Страниц: 174
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

This book introduces C++ programmers to the world of Machine Learning. If you know C++ but haven't worked with Machine Learning solutions before, this book is a good place to start learning the basics and experimenting with the language's essential concepts and techniques. The book starts off by showing you how to set up a development environment and put together some basic neural networks using the Flashlight library. It then covers essential tasks like data preprocessing, model training, and evaluation, with practical examples that show how Machine Learning works in a C++ context. You will also learn strategies for dealing with common problems like overfitting and performance optimization. The next few chapters get into more complex topics like convolutional neural networks, model deployment, and some key performance tuning techniques. This will help you develop and integrate your own models into applications. One of the positive aspects of using C++ for Machine Learning is its ability to execute code at blazing speeds.