Opening book details…
Can I read Building Machine Learning Pipelines on EtoBox?
Building Machine Learning Pipelines by Hannes Hapke [Hapke, Hannes] is a nonfiction available to read on EtoBox.
What is Building Machine Learning Pipelines about?
Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems.Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects.Understand the steps to build a machine learning pipelineBuild your pipeline using components from TensorFlow ExtendedOrchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow...
Who reads Building Machine Learning Pipelines?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Hannes Hapke [Hapke, Hannes]
- Publisher
- O'Reilly Media
- Published
- 2020
- Language
- EN
- Category
- nonfiction
- Subjects
- Engineering, Computer Technology, Stem
More by Hannes Hapke [Hapke, Hannes]
Browse all works by Hannes Hapke [Hapke, Hannes]
Similar books
- Operationalizing Machine Learning Pipelines: Building Reusable and Reproducible Machine Learning Pipelines Using MLOps — Vishwajyoti Pandey; Shaleen Bengani (2022)
- Machine Learning Production Systems : Engineering Machine Learning Models and Pipelines — Robert Crowe, Hannes Hapke, Emily Caveness, Di Zhu, Catherine Nelson (2025)
- Machine Learning on Kubernetes : A Practical Handbook for Building and Using a Complete Open Source Machine Learning Platform on Kubernetes — FAISAL. BRIGOLI MASOOD (ROSS.); Ross Brigoli (2022)
- Machine Learning for Mobile : Practical Guide to Building Intelligent Mobile Applications Powered by Machine Learning — Avinash Venkateswarlu Revathi Gopalakrishnan (2018)
- Building Machine Learning Systems with Python — Luis Pedro Coelho Willi Richert (2013)
- Data Science on AWS : Implementing End-to-end, Continuous AI and Machine Learning Pipelines — Fregly, Chris, Barth, Antje (2021)