Name: Active Learning to Minimize the Possible Risk of Future Epidemics (en Inglés)
SKU: 59612327
Price: 171128.00 COP
Availability: InStock
Author: Santosh, Kc ; Nakarmi, Suprim
ISBN: 9789819974412

portada Active Learning to Minimize the Possible Risk of Future Epidemics (en Inglés)

Active Learning to Minimize the Possible Risk of Future Epidemics (en Inglés)

Formato

Libro Físico

Autor

Kc Santosh

Suprim Nakarmi

Editorial

Springer

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

23.4x15.6x0.6 cm

Peso

0.17 kg.

ISBN13

9789819974412

Categorías

Ingeniería: general
Bases de datos
Inteligencia artificial

Active Learning to Minimize the Possible Risk of Future Epidemics (en Inglés)

Kc Santosh (Autor) · Suprim Nakarmi (Autor) · Springer · Tapa Blanda

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Reseña del libro "Active Learning to Minimize the Possible Risk of Future Epidemics (en Inglés)"

Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big enough to effectively tackle future epidemics? In this context, active learning, often referred to as human or expert-in-the-loop learning, becomes imperative, enabling machines to commence learning from day one with minimal labeled data. In unsupervised learning, the focus shifts toward constructing advanced machine learning models like deep structured networks that autonomously learn over time, with human or expert intervention only when errors occur and for limited data--a process we term mentoring. In the context of Covid-19, this book explores the use of deep features to classify data into two clusters (0/1: Covid-19/non-Covid-19) across three distinct datasets: cough sound, Computed Tomography (CT) scan, and chest x-ray (CXR). Not to be confused, our primary objective is to provide a strong assertion on how active learning could potentially be used to predict disease from any upcoming epidemics. Upon request (education/training purpose), GitHub source codes are provided.