|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Wasmedge||6,655||7||13 hours ago||18||August 07, 2023||286||apache-2.0||C++|
|WasmEdge is a lightweight, high-performance, and extensible WebAssembly runtime for cloud native, edge, and decentralized applications. It powers serverless apps, embedded functions, microservices, smart contracts, and IoT devices.|
|Yao||6,401||13 hours ago||18||May 18, 2023||72||apache-2.0||Go|
|:rocket: A performance app engine to create web services and applications in minutes.Suitable for AI, IoT, Industrial Internet, Connected Vehicles, DevOps, Energy, Finance and many other use-cases.|
|Resource scheduling and cluster management for AI|
|Computer Science Resources||2,119||3 months ago||6|
|A list of resources in different fields of Computer Science|
|🦄 The Enterprise™ programming language|
|Cloudml Samples||1,453||2 years ago||apache-2.0||Python|
|Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples|
|Deep Learning In Production||949||5 months ago||1||Jupyter Notebook|
|Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.|
|Practical Deep Learning Book||675||25 days ago||17||mit||Jupyter Notebook|
|Official code repo for the O'Reilly Book - Practical Deep Learning for Cloud, Mobile & Edge|
|Model_server||593||11 hours ago||2||March 25, 2022||30||apache-2.0||C++|
|A scalable inference server for models optimized with OpenVINO™|
|Deep Learning In Cloud||540||7 months ago||mit|
|List of Deep Learning Cloud Providers|
Welcome to the AI Platform Training and Prediction sample code repository. This repository contains samples for how to use AI Platform for model training and serving.
The repository is organized by tasks:
Each task can be broken down to general usage
(CPU/GPU) to specific features:
Scroll down to see what we have available, each task may provide a notebook or code solution. Where the code solution will have a
README guide and the notebook solution is a full walkthrough. Our code guides are designed to provide you with the code and instructions on how to run the code, but leave you to do the digging, where our notebook tutorials try to walk you through the whole process by having the code available in the notebook throughout the guide.
If you dont see something for the task youre trying to complete, please head down to our section What do you want to see?
For installation instructions and overview, please see the documentation. Please refer to
README.md in each sample directory for more specific instructions.
Tensor Processing Units (TPUs) are Googles custom-developed ASICs used to accelerate machine-learning workloads. You can run your training jobs on AI Platform, using Cloud TPU.
TensorFlow Estimator Trainer Package Template - When training a Tensorflow model, you have to create a trainer package, here we have a template that simplifies creating a trainer package for AI Platform. Take a look at this list with some introductory examples.
Tensorflow: Cloud TPU Templates - A collection of minimal templates that can be run on Cloud TPUs on Compute Engine, Cloud Machine Learning, and Colab.
Please see the Cloud TPU guide for how to use Cloud TPU.
If you came looking for a sample we dont have, please file an issue using the Sample / Feature Request template on this repository. Please provide as much detail as possible about the AI Platform sample you were looking for, what framework (Tensorflow, Keras, scikit-learn, XGBoost, PyTorch...), the type of model, and what kind of dataset you were hoping to use!
Jump below if you want to contribute and add that missing sample.
We welcome external sample contributions! To learn more about contributing new samples, checkout our CONTRIBUTING.md guide. Please feel free to add new samples that are built in notebook form or code form with a README guide.
Want to contribute but don't have an idea? Check out our Sample Request Page and assign the issue to yourself so we know you're working on it!
We host AI Platform documentation here
The content in the
CloudML-Samples repository is not officially maintained by Google.