Apache MXNet
Apache MXNet is a retired deep learning framework (now in the Apache Attic) designed for both efficiency and flexibility. It provided a multi-language API for building and training deep neural networks with support for distributed training, the Gluon high-level API, and deployment on edge devices. MXNet supported Python, Scala, Java, C++, R, Julia, and Perl.
Apache MXNet publishes 1 API on the APIs.io network. Tagged areas include AI, Deep Learning, Machine Learning, Neural Networks, and Python.
Apache MXNet’s developer surface includes developer portal and 9 more developer resources.
Kin Score
APIs 1
Individual APIs this provider publishes, each with its own machine-readable definition.
Apache MXNet
MXNet provides APIs in Python, Scala, Java, C++, R, Julia, and Perl for deep learning model development, with the Gluon high-level API for imperative model building, Symbol/NDAr...
Pricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Apache Mxnet Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals for API financial operations.
Apache Mxnet Finops
FINOPSFeatures 8
Notable capabilities this provider offers.
Hybrid Front-End
Seamlessly transitions between Gluon eager imperative mode and symbolic execution for research flexibility and production efficiency.
Distributed Training
Supports Parameter Server and Horovod for scalable distributed training across multiple GPUs and nodes.
Multi-Language Bindings
Native APIs in Python, Scala, Java, C++, R, Julia, Clojure, and Perl for broad developer accessibility.
Gluon High-Level API
Intuitive Gluon API for imperative model building with automatic differentiation and dynamic computation graphs.
NDArray API
NumPy-like array operations for GPU-accelerated numerical computing as the foundation of MXNet computations.
Symbol API
Symbolic computation graph API for efficient inference and production deployment.
Model Zoo
Pre-trained models for computer vision, NLP, and other tasks accessible via the Gluon model zoo.
Edge Deployment
Lightweight deployment support for edge devices and mobile platforms via TVM and ONNX export.
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Security Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Use Cases 5
What developers build with this provider.
Computer Vision
Build and train image classification, object detection, and segmentation models using GluonCV toolkit.
Natural Language Processing
Develop NLP models for text classification, sentiment analysis, and language modeling using GluonNLP.
Time Series Forecasting
Build time series forecasting models using the GluonTS toolkit for probabilistic forecasting.
Distributed Deep Learning
Train large neural networks across multiple GPUs and nodes using Parameter Server or Horovod.
Research Prototyping
Rapid prototyping of novel deep learning architectures using the Gluon imperative API.
Integrations 7
Pre-built integrations with other platforms and tools.
GluonCV
Computer vision toolkit built on MXNet providing pre-trained models and training utilities for vision tasks.
GluonNLP
NLP toolkit built on MXNet with pre-trained language models and text processing utilities.
GluonTS
Time series modeling toolkit built on MXNet for probabilistic forecasting.
ONNX
ONNX model format support for importing and exporting models to/from other frameworks.
TVM
Apache TVM deep learning compiler for optimizing MXNet model deployment on diverse hardware targets.
Horovod
Horovod distributed training framework integration for efficient multi-GPU and multi-node training.
D2L.ai
Dive into Deep Learning interactive textbook using MXNet for teaching deep learning concepts.
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Resources
Get Started 1
Portal, sign-up, and the first successful call
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Other 2
Properties that don't map to a standard resource type