Deep Netts Releases Professional Version 3.0 for Java Developers to Deploy TensorFlow Machine Learning Models Using Java
— Dr. Zoran Sevarac, Java Champion and Co-Founder of Deep Netts
LAS VEGAS, NEVADA, USA, Oct. 17, 2022 /EINPresswire.com/ — At JavaOne, the premier technical conference for the global Java developer community, Deep Netts today introduced Deep Netts Professional version 3.0. Deep Netts Professional Version 3.0 is a lightweight, user-friendly software tool that allows Java developers to easily build/deploy machine learning (ML) models directly in Java. Version 3.0 is the fastest native Java implementation of deep learning and allows developers to integrate ML models created with Python/TensorFlow directly into their native or traditional Java application server systems.
Unlike other software that uses low-level C/C++ toolkits or requires deep data science expertise, Deep Netts increases developer productivity by using standard constructs familiar to all Java developers. Version 3.0 extends 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 native Java 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 care health, system 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 integrated into all applications, from server to front-end UI. Java is the main programming language used by millions of global developers to create 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.