Automated Machine Learning: Methods, Systems, Challenges
Frank Hutter, Joaquin Vanschoren, Lars Kotthoff
Informasi Umum
Kode
22.21.1377
Klasifikasi
006.31 - Machine Learning
Jenis
Buku - Elektronik (E-Book)
Subjek
Machine Learning
No. Rak
Dilihat
196 kali
Informasi Lainnya
Abstraksi
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Koleksi & Sirkulasi
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Pengarang
| Nama | Frank Hutter, Joaquin Vanschoren, Lars Kotthoff |
| Jenis | Perorangan |
| Penyunting | |
| Penerjemah |
Penerbit
| Nama | Springer |
| Kota | New York |
| Tahun | 2019 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
