is a flexible and efficient library for deep learning.
Building a high-performance deep learning library requires many system-level design decisions. In this design note, we share the rationale for the specific choices made when designing MXNet. We imagine that these insights may be useful to both deep learning practioners and builders of other deep learning systems.
Introducing - Gluon
We’re happy to introduce a new elegant, easy to use, imperative interface for MXNet.
Learn MoreMXNet 0.11.0 Released
We're excited to announce the release of MXNet 0.11.0! Check out the release notes for latest updates.
Learn MoreMXNet Joining Apache
We’re excited to announce that MXNet has been accepted to the Apache Incubator.
Learn MoreModel Zoo
Off the shelf pre-trained models. Fast implementations of many state-of-art models.
Examples
Explore projects from simple demos, exmaples, tutorials to state-of-the-art research.
Tutorials
These tutorials introduce a few fundamental concepts in deep learning and how to implement them in MXNet.
Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.