000			01573nam a2200217Ia 4500
003			NULRC
005			20250520102950.0
008			250520s9999 xx 000 0 und d
020			_a9783030053178
040			_cNULRC
050			_aQ 325.5 .A98 2019
245		0	_aAutomated machine learning : _bmethods, systems, challenges / _cedited by Frank Hutter, Lars Kotthoff, and Joaquin Vanschoren
260			_aSwitzerland : _bSpringer, _cc2019
300			_axiv, 219 pages : _billustrations ; _c24 cm
504			_aIncludes bibliographical references.
505			_aPart I : AutoML methods -- 1. Hyperparameter optimization -- 2. Meta-learning -- 3. Neural architecture search -- Part II : AutoML systems -- 4. Auto-WEKA : automatic model selection and hyperparameter optimization in WEKA -- 5. Hyperopt-sklearn -- 6. Auto-sklearn : efficient and robust automated machine learning -- 7. Towards automatically-tuned deep neural networks -- 8. TPOT : A Tree-based pipeline optimization tool for automating machine learning -- 9. The Automatic statistician -- Part II : AutoML challenges -- 10. Analysis of the autoML challenge series 2015-2018
520			_aThis open access book presents the first comprehensive overview of general methods in autmated machine learning (AutoML), collects descriptions of existing systems based on these methiods, and discusses the first series of international challenges of AutoML systems.
650			_aARTIFICIAL INTELLIGENCE
700			_aHutter, Frank ;Kotthoff, Lars;Vanschoren, Joaquin _eeditor;co-editor;co-editor
942			_2lcc _cBK
999			_c20016 _d20016