Automated Machine Learning in Action

Häftad, Engelska, 2022

365 kr

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Beskrivning

Optimize every stage of your machine learning pipelines with powerful automation components and cutting-edge tools like AutoKeras and KerasTuner. Automated Machine Learning in Action, filled with hands-onexamples and written in an accessible style, reveals how premade machine learning components can automate time-consuming ML tasks.

Automated Machine Learning in Action teaches you to automate selecting the best machine learning models or data preparation methods for your own machine learning tasks, so your pipelines tune themselves without needing constant input. You'll quickly run through machine learning basics thatopen upon AutoML to non-data scientists, before putting AutoML into practicefor image classification, supervised learning, and more.

Automated machine learning (AutoML) automates complex andtime-consuming stages in a machine learning pipeline with pre packaged optimal solutions. This frees up data scientists from data processing and manualtuning, and lets domain experts easily apply machine learning models to their projects.

Produktinformation

Utgivningsdatum:2022-06-01
Mått:186 x 234 x 22 mm
Vikt:620 g
Format:Häftad
Språk:Engelska
Antal sidor:300
Upplaga:1
Förlag:Pearson Education
ISBN:9781617298059

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Programmeringsböcker inom Data och IT
Informationsteknik: allmänt inom Data och IT

Mer om författaren

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.

Recensioner i media

“Automating automation itself is a new concept and this book does justice to it in terms of explaining the concepts, sharing real world advancements, use cases and research related to the topic. “ Satej KumarSahu “A book with a lot of promise, covering a topic that's like to become hot in the next year or so. Read this now, and get ahead of the curve!” RichardVaughan “A nice introduction to AutoML, its ambitions, and challenges bothin theory and in practice.” Alain Couniot “Helps you to clearly understand the process of Machine Learning automation. The examples are clear, concise, and applicable to the real world.”Walter Alexander Mata López “The author's friendly style makes novices feel ready to try outAutoML tools.” Gaurav Kumar Leekha “A great book to take your machine learning skills to the next level.” Harsh Raval “An impressive effort by the authors to break down a complex MLtopic into understandable chunks.” Venkatesh Rajagopal