O'Reilly's "Deep Learning: A Practitioner's Approach" (2017)
Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. .
The book is currently cited by 14 academic research papers as tracked by the ACM.
This book has also been translated into (at least) 7 different world languages.
O'Reilly's "Kubeflow Operations Guide" (2021)
Kubeflow (https://www.kubeflow.org/) is an open source Kubernetes-native platform for developing, orchestrating, deploying, and running scalable and portable machine learning workloads. It is a cloud native platform based on Google’s internal machine learning (ML) pipelines. The project is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable.
In this book we take a look at the evolution of machine learning in enterprise, how infrastructure has changed, and then how Kubeflow meets the needs of the modern enterprise.
This book currently boasts 2 different translations.
- Buy the book on Amazon.com
- Buy the book from O'Reilly Books Online (30% off with this link)
Wired Magazine Coverage
Our founder Josh Patterson has been quoted in wired.com in past years.
Select O'Reilly.com Articles
Below we highlight some of our team's articles posted on O'Reilly.com over the years.
- Article: Integrating convolutional neural networks into enterprise applications, ("Building a production-grade real-time image classification system.")
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