Practical Deep Learning at Scale with MLflow

Bridge the gap between offline experimentation and online production

; Dr. Matei Zaharia

This book teaches you how to use MLflow to support deep learning life cycle development with step-by-step instructions. You'll build NLP solutions from scratch and implement scalable deep learning pipelines from initial offline experimentation to production with coherent provenance tracking for code, data, models, and explainability. Les mer
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528,-

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Leveringstid: Sendes innen 21 dager

Paperback
Legg i
Paperback
Legg i
Vår pris: 528,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager

This book teaches you how to use MLflow to support deep learning life cycle development with step-by-step instructions. You'll build NLP solutions from scratch and implement scalable deep learning pipelines from initial offline experimentation to production with coherent provenance tracking for code, data, models, and explainability.
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Utgitt:
Forlag: Packt Publishing Limited
Innbinding: Paperback
Språk: Engelsk
ISBN: 9781803241333
Format: 9 x 8 cm
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Yong Liu has been working in big data science, machine learning, and optimization since his doctoral student years at the University of Illinois at Urbana-Champaign (UIUC) and later as a senior research scientist and principal investigator at the National Center for Supercomputing Applications (NCSA), where he led data science R&D projects funded by the National Science Foundation and Microsoft Research. He then joined Microsoft and AI/ML start-ups in the industry. He has shipped ML and DL models to production and has been a speaker at the Spark/Data+AI summit and NLP summit. He has recently published peer-reviewed papers on deep learning, linked data, and knowledge-infused learning at various ACM/IEEE conferences and journals.