Adaptive Computation and Machine Learning series: Knowledge Graphs
Fundamentals, Techniques, and Applications
Ocena książki
Parametry
- 568 stron
- 20 godzin czytania
Więcej o książce
A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence.The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.
Zakup książki
Adaptive Computation and Machine Learning series: Knowledge Graphs, Mayank Kejriwal, Craig A. Knoblock, Pedro Szekely
- Język
- Rok wydania
- 2021
- Oprawa
- (twarda)
Metody płatności
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- Tytuł
- Adaptive Computation and Machine Learning series: Knowledge Graphs
- Podtytuł
- Fundamentals, Techniques, and Applications
- Język
- angielski
- Wydawca
- MIT Press
- Rok wydania
- 2021
- Oprawa
- twarda
- Liczba stron
- 568
- ISBN10
- 0262045095
- ISBN13
- 9780262045094
- Seria
- Kategorie
- Tagi
- Biznes, Nauki przyrodnicze, Tematyka psychologiczna, Tematyka filozoficzna, Nauka, Technologia, Edukacja & Szkolnictwo, Szkoła, Społeczeństwo, Przywództwo, Komunikacja, Kultura, Zatrudnienie, Inżynieria, Przyszłość, Internet, Ewolucja, Sztuczna inteligencja, Neurobiologia, Mózg, Świadomość, Strategia, Innowacje, Bazy danych, Algorytmy, Myślenie krytyczne, Robotyka, Uczenie maszynowe, Hacking
- Ocena
- 3,5 z 5
- Opis
- A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence.The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.