| ray-project/ray |
29,596 |
|
80 |
363 |
about 2 years ago |
95 |
December 04, 2023 |
3,528 |
apache-2.0 |
Python |
| Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads. |
| zergtant/pytorch-handbook |
18,594 |
|
0 |
0 |
over 2 years ago |
0 |
|
52 |
|
Jupyter Notebook |
| pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行 |
| aws/amazon-sagemaker-examples |
9,221 |
|
0 |
0 |
about 2 years ago |
0 |
|
894 |
apache-2.0 |
Jupyter Notebook |
| Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker. |
| google-research/vision_transformer |
8,669 |
|
0 |
0 |
about 2 years ago |
0 |
|
123 |
apache-2.0 |
Jupyter Notebook |
| NielsRogge/Transformers-Tutorials |
6,731 |
|
0 |
0 |
about 2 years ago |
0 |
|
237 |
mit |
Jupyter Notebook |
| This repository contains demos I made with the Transformers library by HuggingFace. |
| alexcasalboni/aws-lambda-power-tuning |
4,956 |
|
0 |
0 |
about 2 years ago |
0 |
|
11 |
apache-2.0 |
JavaScript |
| AWS Lambda Power Tuning is an open-source tool that can help you visualize and fine-tune the memory/power configuration of Lambda functions. It runs in your own AWS account - powered by AWS Step Functions - and it supports three optimization strategies: cost, speed, and balanced. |
| anvaka/VivaGraphJS |
3,676 |
|
31 |
9 |
about 2 years ago |
29 |
October 27, 2019 |
115 |
other |
JavaScript |
| Graph drawing library for JavaScript |
| microsoft/FLAML |
3,500 |
|
0 |
11 |
about 2 years ago |
92 |
October 02, 2023 |
210 |
mit |
Jupyter Notebook |
| A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP. |
| darold/pgbadger |
3,296 |
|
0 |
0 |
about 2 years ago |
0 |
|
19 |
postgresql |
Perl |
| A fast PostgreSQL Log Analyzer |
| justmarkham/scikit-learn-videos |
3,180 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| Jupyter notebooks from the scikit-learn video series |
