Build and deploy machine learning models in Java easily

Java based Deep Learning enterprise solution
empowering and accelerating your AI journey

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Are you Java Developer looking to enhance your application with modern AI?
Are you confused with support for Deep Learning in Java? Have technical issues with integration into your app?
Deep Netts provides intuitive API, easy to use tools and pure Java solution which solves technical issues for your project.

Deep Learning IDE

Intuitive visual developer tool for deep learning that provides wizard based step by step guideance, drag n'drop network architecture builder and visual debugging.
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Embedded Deep Learning for Java Apps and Devices

Pure Java deep learning library simplifies distribution of AI models and solves technical problems with integration into existing apps, mobile and edge devices. Learn more >

Java Technology Standard

Java-friendly API, base for the official Java Technology standard JSR381 for visual recognition and machine learning.
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What can you do using Deep Netts?


Classify data items, text, users, banner clicks, transactions into a set of predefined categories. The most commonly used machine learning task which can help automate manual steps, increase productivity and efficency of your business processes.

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Predict numeric values in order to make better decisions, optimize costs or resource usage. Even rough estimation is better than nothing for managing complex processes.

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Image Recognition

Categorize or recognize objects in images with great precission using state of the art convolutional neural networks.

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Anomally Detection

Detect unusual patterns that deviate from common, expected behaviour.

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Why Deep Netts?


Java Developer Friendly

Quickly build and use AI in your apps using only your Java skills. The fastest way for Java developers without experience with machine learning, to start using advanced AI. Learn more >


Simple integration

Easy integration thanks to pure Java implementation, without dependencies to native libraries and specialized hardware also makes it easy to use in production and maintain.


Rich tool support

Great user experience with friendly tools for users with software development background.


Deep Netts is a uniquely powerful environment for modern AI development that is simultaneouy approachable, friendly, and easy to get started with for beginners, and it works with OpenJDK!

Geertjan Wielenga

Senior Director of OS Projects

Azul Systems
As a Java developer, I have especially come to appreciate having a tool in my language that I could immediately use out of the box and not have to add on weeks, or even months, of training

Oscar Bastidas, Ph.D.

Postdoctoral Research Associate

University of Minnesota

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If you are a Java software developer and are looking for an ML framework that is Java-centric and is compatible with the Android operating system, I suggest you definitely consider using DeepNetts. It is a lightweight Java library, easy to learn, and solves many technical challenges related to ML.

Krasimir Topchiyski,

Software Developer

MetaTrans Games

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Our Partners

Azul provides the world’s most trusted Java platform, delivered by the world’s most expert Java engineering team. Deep Netts provides distribution that includes embedded Azul Open JDK build for the best user experience and performance.

The JCP is the mechanism for developing standard technical specifications for Java technology. As a JCP member Deep Netts actively participates and leads the development of standard for visual recognition using machine learning.

Apache NetBeans is an open source Development Environment, Tooling Platform and Application Framework. Deep Netts uses it as a base for Deep Learning IDE and contributes to Apche NetBeans development.

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Parking lot occupancy detection using deep learning in Java

This tutorial shows you how you can use Deep Netts to create visual parking lot occupancy detection using deep learning in Java.The data set contains labeled images of vacant and occupied parking spaces, extracted from the camera under different light conditions.

Cloud classification using deep learning in Java

This tutorial demonstrates how to perform cloud image classification in Java using deep learning. Cloud image classification is important for many applications, including climate modeling, weather prediction, solar energy production, satellite imaging, satellite communication, and many others.

Why Deep Learning in Java?

#1 Language for AI/ML Developers

Java is a top language for AI and Machine Learning developers, says research study from Evans Data.
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#1 IoT and Edge Platform

With 20% market share Java is the top programming language for IoT development, says research study from Eclipse Foundation.
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#1 Development Platform

Java is used by over 10 million developers, and running on 56 bilion devices.
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