A library for training and deploying machine learning models on Amazon SageMaker
-
Updated
Jun 13, 2024 - Python
A library for training and deploying machine learning models on Amazon SageMaker
An Engine-Agnostic Deep Learning Framework in Java
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
Open standard for machine learning interoperability
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
适用于复杂场景的人脸识别身份认证系统
ncnn is a high-performance neural network inference framework optimized for the mobile platform
Probabilistic time series modeling in Python
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
AI on Hadoop
State-of-the-art 2D and 3D Face Analysis Project
TensorLy: Tensor Learning in Python.
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
The Unified AI Framework
🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
The Java implementation of Dive into Deep Learning (D2L.ai)
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Some Data Science examples using Groovy
Add a description, image, and links to the mxnet topic page so that developers can more easily learn about it.
To associate your repository with the mxnet topic, visit your repo's landing page and select "manage topics."