The Skymind team has announced a milestone release of Eclipse Deeplearning4j (DL4J), an open-source library for deep learning.
DL4J 1.0.0-alpha has some breakthrough changes which will ease development of deep learning applications using Java and Scala. From a developer’s perspective, the roadmap provides an exciting opportunity to perform complex numerical computations with the major updates done to each module of Deeplearning4j.
DL4J is a distributed neural network library in Java and Scala which allows distributed training on Hadoop and Spark. It provides powerful data processing that enables efficient use of CPUs and GPUs. With new features, bug fixes and optimizations in the toolkit, Deeplearning4j provides excellent capabilities to perform advanced deep learning tasks.
Here are some of the significant changes available in DL4J 1.0.0-alpha:
A powerful library used for scientific and numerical computing for the JVM:
An effective ETL library for getting data into the pipeline, so neural networks can understand:
A package for efficient optimization of neural networks to obtain good performance:
A reinforcement learning framework integrated with deeplearning4j for the JVM:
A scala wrapper for DL4J resembling a Keras like API for deep learning:
An open-source Scala bindings for ND4J:
We can expect more improvements and new features on DL4J 1.0.0 roadmap. For the full list of updates, you can refer the release notes.
I remember deciding to pursue my first IT certification, the CompTIA A+. I had signed…
Key takeaways The transformer architecture has proved to be revolutionary in outperforming the classical RNN…
Once we learn how to deploy an Ubuntu server, how to manage users, and how…
Key-takeaways: Clean code isn’t just a nice thing to have or a luxury in software projects; it's a necessity. If we…
While developing a web application, or setting dynamic pages and meta tags we need to deal with…
Software architecture is one of the most discussed topics in the software industry today, and…