Deep Netts Launches Professional Version 3.0 for Java Developers to Deploy TensorFlow Machine Learning Models Using Java

LAS VEGAS, NEVADA, US, October 17, 2022 /EINPresswire.com/ — At JavaOne, the premier technical conference for the global Java developer community, Deep Netts today introduced Version 3.0 of Deep Netts Professional. Version 3.0 of Deep Netts Professional is a lightweight, developer-friendly software tool that enables Java developers to easily build/deploy Machine Learning (ML) models directly in Java. Version 3.0 is the fastest Java-native implementation of deep learning and allows developers to embed ML models created with Python/TensorFlow directly into their Java cloud-native or traditional application server systems.

Unlike other software that uses low-level C/C++ toolkits or requires extensive data science expertise, Deep Netts increases developer productivity using standard constructs familiar to all Java developers. Version 3.0 expands the use of pure Java for ML applications beyond the desktop to mobile, cloud-native, and edge IoT use cases.

“Deep Netts is committed to helping the Java community with easy-to-use, Java-native tools that will further expand the use of ML in a wide variety of use cases, from visual recognition with our implementation of JSR 381 VisRec to healthcare, systems performance, cybersecurity, and many other use cases.”
– Dr. Zoran Sevarac, Java Champion and co-Founder of Deep Netts.

ML is a long-term trend and is embedded into all applications from the server to the front-end UI. Java is the leading programming language for millions of global developers to build these applications. Java software developers need easy-to-use tools to build effective ML applications without relying on complex low-level libraries or unfamiliar programming paradigms.

Zoran Sevarac
Deep Netts
contact@deepnetts.com