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Bringing the World of Deep Learning to Java
By Kesha Williams, Mikhail Shapirov, Qing Lan, Vaibhav Goel and Raja Hafiz Affandi
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Machine Learning in Java is Speeding Image Processing
Amazon's Deep Java Library (DJL) is one of several implementations of the new JSR 381 standard for building machine learning applications in Java.
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A Guide to Using NDArrays in Java
Leverage the NDArray from Deep Java Library (DJL) to write your NumPy code in Java and apply NDArray into a real-world application.
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Using Deep Java Library to do Machine Learning on SpringBoot
Java users can integrate ML into their Spring applications with Spring Boot Starter for Deep Java Library. Apply these frameworks to integrate ML capabilities into microservices for deep learning.
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A Deep Learning Toolkit Gives Java Developers a Jumpstart
Amazon releases Deep Java Library (DJL), providing Java developers a jumpstart with deep learning.
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Detecting Pneumonia From Chest X-Ray Images in Java
Use Deep Java Library (DJL) for image classification to apply deep learning to assist with clinical decision making.
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How Amazon Retail Systems Run Machine Learning Predictions with Apache Spark
Amazon Retail systems uses Apache Spark with Deep Java Library (DJL) to build propensity models to drive customer experience.
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Run a Deep Learning Model in Java: A Quick Take
We are excited to announce the Deep Java Library (DJl), an open source library to develop, train and run Deep learning models in Java using intuitive, high-level APIs.
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Deploying Deep Learning in Production Gains Multiple Efficiencies
TalkingData, a data intelligence provider, uses Deep Java Library with Apache Spark for machine learning inference to reduce time-to-market.
