System Design for Epidemics Using Machine Learning and Deep Learning, Kanagachidambaresan
Автор: Abraham Varghese, Eduardo M. Lacap, Ibrahim Sajath, Kamal Kumar, Shajidmon Kolamban Название: Controlling Epidemics with Mathematical and Machine Learning Models ISBN: 1668478846 ISBN-13(EAN): 9781668478844 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 35343.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides mathematical and machine learning models for epidemical diseases, with special attention given to the COVID-19 pandemic. The book gives mathematical proof of the stability and size of diseases, and covers topics such as compartmental models, reproduction number, and SIR model simulation.
Автор: Garg Lalit, Chakraborty Chinmay, Mahmoudi Saпd Название: Healthcare Informatics for Fighting Covid-19 and Future Epidemics ISBN: 3030727513 ISBN-13(EAN): 9783030727512 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents innovative solutions utilising informatics to deal with various issues related to the COVID-19 outbreak.
Описание: This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems.
Автор: Bonaccorso Giuseppe Название: Hands-On Unsupervised Learning with Python ISBN: 1789348277 ISBN-13(EAN): 9781789348279 Издательство: Неизвестно Рейтинг: Цена: 9562.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Unsupervised learning is a key required block in both machine learning and deep learning domains. You will explore how to make your models learn, grow, change, and develop by themselves whenever they are exposed to a new set of data. With this book, you will learn the art of unsupervised learning for different real-world challenges.
Описание: Machine learning allows models or systems to learn without being explicitly programmed. You will see how to use the best of libraries support such as scikit-learn, Tensorflow and much more to build efficient smart systems.
Автор: Fandango Armando Название: Mastering TensorFlow ISBN: 1788292065 ISBN-13(EAN): 9781788292061 Издательство: Неизвестно Рейтинг: Цена: 7171.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: We cover advanced deep learning concepts (such as transfer learning, generative adversarial models, and reinforcement learning), and implement them using TensorFlow and Keras. We cover how to build and deploy at scale with distributed models. You will learn to build TensorFlow models using R, Keras, TensorFlow Learn, TensorFlow Slim and Sonnet
Описание: This book is designed to guide you through TensorFlow 2 and how to use it effectively. Throughout the book, you will work through recipes and get hands-on experience to perform complex data computations, gain insights into your data, and more.
Описание: You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.
Описание: This book equips readers with the knowledge to data analytics, machine learning and deep learning techniques for applications defined under the umbrella of Industry 4.0.
Автор: Ceja, Enrique Garcia Название: Behavior analysis with machine learning using r ISBN: 1032067047 ISBN-13(EAN): 9781032067049 Издательство: Taylor&Francis Рейтинг: Цена: 12707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records.
Описание: This book uses real-life datasets from Kaggle to explain basic statistics for machine learning for data segmentation, regression predictions, and forecasts. You`ll focus on variable dependency and autocorrelation to build, test, and use a linear regression prediction model and time series forecasts.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
