mlToolKits
TensorFlowOnSpark
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| mlToolKits | TensorFlowOnSpark | |
|---|---|---|
| 1 | 2 | |
| 74 | 3,863 | |
| - | 0.1% | |
| 0.0 | 1.4 | |
| 11 months ago | 10 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mlToolKits
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Someone with a good experience in python can rate my code?
https://github.com/learningOrchestra/learningOrchestra/blob/552994056f2415ee54c24f2e1101fcca7fbd694b/microservices/code_executor_image/utils.py#L93-L94
TensorFlowOnSpark
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[D]Speed up inference on Spark
Currently I use TensorflowOnSpark frame to train and predict model. When prediction, I have billions of samples to predict which is time-consuming. I wonder if there is some good practices on this.
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[D] Plug or Integrate a GNN Pytorch code base into Spark Cluster
https://github.com/yahoo/TensorFlowOnSpark : check out if this project is useful for you.
What are some alternatives?
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
ecosystem - Integration of TensorFlow with other open-source frameworks
docker-etcd-cluster - Very simple etcd cluster powered by docker compose
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
swarm-kit - 🔥 Self-Hosted Docker Swarm Toolkit
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Contra - Contra is a lightweight, production ready Tensorflow alternative for solving time series prediction challenges with AI
Keras - Deep Learning for humans
listenbrainz-server - Server for the ListenBrainz project, including the front-end (javascript/react) code that it serves and all of the data processing components that LB uses.
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
docker-stack-deploy - Utility to improve docker stack deploy
dcos - DC/OS - The Datacenter Operating System