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.
Epub (Kobo), Epub (Adobe)
Publication Date: 10/07/2021
- ISBN:
- 9783030688172
- 9783030688172
- Category:
- Data mining
- Format:
- Epub (Kobo), Epub (Adobe)
- Publication Date:
- 10-07-2021
- Language:
- English
- Publisher:
- Springer International Publishing
This item is delivered digitally
Great!
Click on Save to My Library / Lists
Click on Save to My Library / Lists
Select the List you'd like to categorise as, or add your own
Here you can mark if you have read this book, reading it or want to read
Awesome! You added your first item into your Library
Great! The fun begins.
Click on My Library / My Lists and I will take you there
Click on My Library / My Lists and I will take you there
Reviews
Be the first to review Representation Learning.
Share This eBook: