Zum Hauptinhalt springen
Dekorationsartikel gehören nicht zum Leistungsumfang.
Automated Machine Learning in Action
Taschenbuch von Haifeng Jin (u. a.)
Sprache: Englisch

55,40 €*

inkl. MwSt.

Versandkostenfrei per Post / DHL

Lieferzeit 1-2 Wochen

Kategorien:
Beschreibung

Optimize every stage of your machine learning pipelines with powerful automation components and cutting-edge tools like AutoKeras and KerasTuner.

In Automated Machine Learning in Action you will learn how to:

  • Improve a machine learning model by automatically tuning its hyperparameters
  • Pick the optimal components for creating and improving your pipelines
  • Use AutoML toolkits such as AutoKeras and Keras Tuner
  • Design and implement search algorithms to find the best component for your ML task
  • Accelerate the AutoML process with data-parallel, model pre-training, and other techniques

Automated Machine Learning in Action reveals how premade machine learning components can automate time-consuming ML [...]'s written in a math-lite and accessible style, and filled with hands-on examples for applying AutoML techniques to every stage of a pipeline. You'll use tools like AutoKeras to create pipelines that automatically select the best approach for your task, remove the burden of manual tuning, and can even be implemented by machine learning novices!

Optimize every stage of your machine learning pipelines with powerful automation components and cutting-edge tools like AutoKeras and KerasTuner.

In Automated Machine Learning in Action you will learn how to:

  • Improve a machine learning model by automatically tuning its hyperparameters
  • Pick the optimal components for creating and improving your pipelines
  • Use AutoML toolkits such as AutoKeras and Keras Tuner
  • Design and implement search algorithms to find the best component for your ML task
  • Accelerate the AutoML process with data-parallel, model pre-training, and other techniques

Automated Machine Learning in Action reveals how premade machine learning components can automate time-consuming ML [...]'s written in a math-lite and accessible style, and filled with hands-on examples for applying AutoML techniques to every stage of a pipeline. You'll use tools like AutoKeras to create pipelines that automatically select the best approach for your task, remove the burden of manual tuning, and can even be implemented by machine learning novices!

Über den Autor

Qingquan Song, Haifeng Jin, and Dr. Xia Ben Hu are the creators of the AutoKeras automated deep learning library. Qingquan and Haifeng are PhD students at Texas A&M University, and have both published papers at major data mining conferences and journals. Dr. Hu is an associate professor at Texas A&M University in the Department of Computer Science and Engineering, whose work has been utilized by TensorFlow, Apple, and Bing.

Details
Erscheinungsjahr: 2022
Fachbereich: Programmiersprachen
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781617298059
ISBN-10: 1617298050
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Jin, Haifeng
Song, Qingquan
Hu, Xia
Hersteller: Manning Publications
Maße: 234 x 188 x 21 mm
Von/Mit: Haifeng Jin (u. a.)
Erscheinungsdatum: 01.06.2022
Gewicht: 0,516 kg
Artikel-ID: 120270518
Über den Autor

Qingquan Song, Haifeng Jin, and Dr. Xia Ben Hu are the creators of the AutoKeras automated deep learning library. Qingquan and Haifeng are PhD students at Texas A&M University, and have both published papers at major data mining conferences and journals. Dr. Hu is an associate professor at Texas A&M University in the Department of Computer Science and Engineering, whose work has been utilized by TensorFlow, Apple, and Bing.

Details
Erscheinungsjahr: 2022
Fachbereich: Programmiersprachen
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781617298059
ISBN-10: 1617298050
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Jin, Haifeng
Song, Qingquan
Hu, Xia
Hersteller: Manning Publications
Maße: 234 x 188 x 21 mm
Von/Mit: Haifeng Jin (u. a.)
Erscheinungsdatum: 01.06.2022
Gewicht: 0,516 kg
Artikel-ID: 120270518
Warnhinweis