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Ditemukan 8 dari pencarian Anda melalui kata kunci: subject="MACHINE LEARNING"
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cover
Data Science and Machine Learning: Mathematical and Statistical Methods
Komentar Bagikan
Dirk P. KroeseZdravko I. BotevThomas TaimreRadislav Vaisman

Edisi
-
ISBN/ISSN
978-1-138-49253-0
Deskripsi Fisik
xxi, 494 hlm.
Judul Seri
-
No. Panggil
-

Edisi
-
ISBN/ISSN
978-1-138-49253-0
Deskripsi Fisik
xxi, 494 hlm.
Judul Seri
-
No. Panggil
-
cover
Statistical and Machine-Learning Data Mining: Techniques for Better Predictiv…
Komentar Bagikan
Bruce Ratner

Edisi
3rd Edition
ISBN/ISSN
978-1-4987-9760-3
Deskripsi Fisik
xxxiii, 643 hlm.
Judul Seri
-
No. Panggil
-

Edisi
3rd Edition
ISBN/ISSN
978-1-4987-9760-3
Deskripsi Fisik
xxxiii, 643 hlm.
Judul Seri
-
No. Panggil
-
cover
Orthogonality in Quantum-ProbabilisticMachine Learning: An Investigation onMu…
Komentar Bagikan
Sheng-Chen BaiKun ZhangShi-Ju Ran

The “black-box” nature of deep learning models fundamentally limits their reliability in critical applications.Tensor networks (TNs), drawing on their interpretable, quantum-probabilistic foundations, offer a promisingpathway toward more transparent machine learning (ML). However, a systematic understanding of theircapabilities and limitations remains an open challenge. Here, we establish a…

Edisi
-
ISBN/ISSN
-
Deskripsi Fisik
10 hlm.
Judul Seri
-
No. Panggil
-
cover
Mathematics for Machine Learning
Komentar Bagikan
Marc Peter DeisenrothA. Aldo FaisalCheng Soon Ong

Edisi
-
ISBN/ISSN
-
Deskripsi Fisik
iii, 394 hal.
Judul Seri
-
No. Panggil
-

Edisi
-
ISBN/ISSN
-
Deskripsi Fisik
iii, 394 hal.
Judul Seri
-
No. Panggil
-
cover
Practical Machine Learning and Image Processing: For Facial Recognition, Obje…
Komentar Bagikan
Himanshu Singh

Edisi
-
ISBN/ISSN
978-1-4842-4149-3
Deskripsi Fisik
-
Judul Seri
-
No. Panggil
-

Edisi
-
ISBN/ISSN
978-1-4842-4149-3
Deskripsi Fisik
-
Judul Seri
-
No. Panggil
-
cover
How reliable are retrieval-augmented and standard ChatGPT models to support f…
Komentar Bagikan
Ali PourzangbarMário J. Franca

This paper evaluates the performance of baseline and domain-augmented ChatGPT models for literature-based knowledge support in flood susceptibility mapping (FSM) using machine Learning approaches. To assess this, we designed five key questions related to FSM, with benchmark responses derived from our comprehensive review article (Pourzangbar et al., Journal of Flood Risk Management 18, e70042),…

Edisi
-
ISBN/ISSN
-
Deskripsi Fisik
12 hlm.
Judul Seri
-
No. Panggil
-
cover
MACHINE LEARNING
Komentar Bagikan
Angga Aditya Permana

Edisi
-
ISBN/ISSN
978-623-198-072-4
Deskripsi Fisik
188 hlm
Judul Seri
-
No. Panggil
-

Edisi
-
ISBN/ISSN
978-623-198-072-4
Deskripsi Fisik
188 hlm
Judul Seri
-
No. Panggil
-
cover
Algoritma Machine Learning Dengan Python
Komentar Bagikan
Joseph Teguh Santoso

Edisi
-
ISBN/ISSN
9 786235 734286
Deskripsi Fisik
49 hlm
Judul Seri
-
No. Panggil
-

Edisi
-
ISBN/ISSN
9 786235 734286
Deskripsi Fisik
49 hlm
Judul Seri
-
No. Panggil
-