Название: Machine Learning for Healthcare: Handling and Managing Data
Автор: Rashmi Agrawal, Jyotir Moy Chatterjee, Abhishek Kumar
Издательство: Chapman and Hall/CRC
Год: 2021
Страниц: 223
Язык: английский
Формат: pdf (true)
Размер: 15.5 MB

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning (ML) is currently causing quite a buzz, and is having a huge impact on healthcare. Payers, providers, and pharmaceutical companies are today seeing applicability in their spaces and are taking advantage of ML. A machine learning model is created by feeding data into a learning algorithm. The algorithm is the place where the magic happens. There are algorithms to determine a patient’s length of stay based on diagnosis, for example, and that algorithm all began when someone decided to write it and train it with true and reliable data.

Название: SAS Programming for Elementary Statistics: Getting Started
Автор: Carla L. Goad
Издательство: CRC Press
Год: 2021
Формат: True PDF
Страниц: 395
Размер: 11.5 Mb
Язык: English

SAS for Elementary Statistics: Getting Started provides an introduction to SAS programming for those who have experience with introductory statistical methods. It is also an excellent programming supplement for an introductory statistics course. It is appropriate for the beginning programmer with no prior SAS experience and the researcher who would like to refresh SAS programming skills.

Название: 2D Game Development with Unity
Автор: Franz Lanzinger
Издательство: CRC Press
Год: 2021
Формат: True PDF
Страниц: 444
Размер: 36.8 Mb
Язык: English

This book teaches beginners and aspiring game developers how to develop 2D games with Unity. Thousands of commercial games have been built with Unity. The reader will learn the complete process of 2D game development, step by step. The theory behind each step is fully explained. This book contains numerous color illustrations and access to all source code and companion videos.

Название: Pattern Language for Game Design
Автор: Christopher Barney
Издательство: CRC Press
Год: 2021
Формат: True PDF
Страниц: 502
Размер: 16.8 Mb
Язык: English

Chris Barney’s Pattern Language for Game Design builds on the revolutionary work of architect Christopher Alexander to show students, teachers, and game development professionals how to derive best practices in all aspects of game design. Using a series of practical, rigorous exercises, designers can observe and analyze the failures and successes of the games they know and love to find the deep patterns that underlie good design. From an in-depth look at Alexander’s work, to a critique of pattern theory in various fields, to a new approach that will challenge your knowledge and put it to work, this book seeks to transform how we look at building the interactive experiences that shape us.

Название: Programming Media Art Using Processing: A Beginner's Guide
Автор: Margaret Noble
Издательство: Chapman and Hall/CRC
Год: 2021
Формат: True PDF
Страниц: 248
Размер: 17.1 Mb
Язык: English

Programming Media Art Using Processing: A Beginner's Guide provides an entry-level exploration into visual design through computer programming using the open source and artist-friendly language, Processing. Used by hundreds of students, this learning system breaks lessons down into strategic steps towards fun and creative media art projects.

Название: Beyond the Worst-Case Analysis of Algorithms
Автор: Tim Roughgarden (Editor)
Издательство: Cambridge University Press
Год: 2021
Формат: True PDF
Страниц: 704
Размер: 10 Mb
Язык: English

There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size.

Название: Beginning Rust: From Novice to Professional
Автор: Milanesi, Carlo
Издательство: Apress
Год: 2018
ISBN: 9781484234686
Формат: epub, pdf
Страниц: XVII, 376
Размер: 5,4 mb
Язык: English

Learn to program with the Rust programming language on Unix, Linux, MacOS, and Windows

Название: Street Coder: The rules to break and how to break them (MEAP Version 2)
Автор: Sedat Kapanoglu
Издательство: Manning Publications Co.
Год: 2020
Формат: True PDF
Страниц: 121
Размер: 13 Mb
Язык: English

Street Coder: Rules to break and how to break them is a guide for beginner programmers making their move from learner to developer. Written by self-taught pro Sedat Kapanoglu, it takes the best practices you learn in a computer science class and deconstructs them to show when they’re beneficial—and when they aren't! The easy-to-follow C# examples easily translate to any modern programming language.

Название: Rust in Action (MEAP Edition Version 10, 15)
Автор: Tim McNamara
Издательство: Manning Publications
Год: 2019-2020
Формат: true pdf, pdf/epub
Страниц: 330, 394
Размер: 13.2 Mb, 11 Mb
Язык: English

Rust in Action introduces the Rust programming language by exploring numerous systems programming concepts and techniques.You'll be learning Rust by delving into how computers work under the hood.

Название: Cloud Native Machine Learning (MEAP Version 5)
Автор: Carl M. Osipov
Издательство: Manning Publications
Год: 2020
Формат: True PDF
Страниц: 149
Размер: 14.9 Mb
Язык: English

Cloud Native Machine Learning is a guide to bringing your experimental machine learning code to production using serverless capabilities from major cloud providers. You’ll start with best practices for your datasets, learning to bring VACUUM data-quality principles to your projects, and ensure that your datasets can be reproducibly sampled. Next, you’ll learn to implement machine learning models with PyTorch, discovering how to scale up your models in the cloud and how to use PyTorch Lightning for distributed ML training. Finally, you’ll tune and engineer your serverless machine learning pipeline for scalability, elasticity, and ease of monitoring with the built-in notification tools of your cloud platform.