Representation Learning - Propositionalization and Embeddings (Hardcover, 1st ed. 2021)

This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning refers to modern data transformation techniques that convert data of different modalities and complexity, including texts, graphs, and relations, into compact tabular representations, which effectively capture their semantic properties and relations. The monograph focuses on (i) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained popularity with recent advances in deep learning. The authors establish a unifying perspective on representation learning techniques developed in these various areas of modern data science, enabling the reader to understand the common underlying principles and to gain insight using selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning researchers and students to developers, software engineers and industrial researchers interested in hands-on AI solutions.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	July 2021
First published:	2021
Authors:	Nada Lavrac • Vid Podpecan • Marko Robnik-Sikonja
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	163
Edition:	1st ed. 2021
ISBN-13:	978-3-03-068816-5
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Databases > Data mining
LSN:	3-03-068816-X
Barcode:	9783030688165

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!