
Build, train, and deploy machine learning models on any JVM using TensorFlow Java.

TensorFlow Java provides a robust API for integrating TensorFlow into JVM environments. It supports both CPU and GPU execution, operating in graph or eager mode. It is designed to leverage the widespread use of Java, Scala, and Kotlin in enterprises for large-scale machine learning adoption. The core component is the tensorflow-core-platform artifact, which includes the Java Core API and native dependencies for supported platforms. Extensions offer specialized support like Intel MKL-DNN and CUDA. It allows for building, saving, loading, and executing TensorFlow models. Example applications include image classification using pre-trained convolutional neural networks, showcasing graph construction, model loading, and graph execution.
TensorFlow Java provides a robust API for integrating TensorFlow into JVM environments.
Explore all tools that specialize in load pre-trained models. This domain focus ensures TensorFlow Java delivers optimized results for this specific requirement.
Explore all tools that specialize in run inference on input data. This domain focus ensures TensorFlow Java delivers optimized results for this specific requirement.
Explore all tools that specialize in utilize java, scala, and kotlin. This domain focus ensures TensorFlow Java delivers optimized results for this specific requirement.
Defines a data flow graph for TensorFlow computations, enabling optimized execution.
Executes operations immediately, providing a more interactive debugging experience.
Allows loading and exporting pre-trained TensorFlow models for seamless integration.
Supports defining custom TensorFlow operations using Java for specialized tasks.
Leverages GPUs and specialized hardware (e.g., Intel MKL-DNN) for accelerated computations.
Install Java 8 or higher.
Configure Maven or Gradle build environment.
Add TensorFlow Java dependency to project's pom.xml or build.gradle.
Select appropriate TensorFlow artifact (CPU, GPU, MKL).
Write Java code using TensorFlow Java API to define and execute computation graphs.
Compile and run the Java application.
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