Made With ML
GokuMohandas
Learn how to develop, deploy and iterate on production-grade ML applications.
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Candidates in this shortlist, not the full registry. GitHub stars belong to repositories, not individual skills.
Results: 10
GokuMohandas
Learn how to develop, deploy and iterate on production-grade ML applications.
lightgbm-org
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and…
tensorflow
An Open Source Machine Learning Framework for Everyone
ray-project
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
dmlc
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask,…
PaddlePaddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
ageron
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
skypilot-org
Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, Slurm, 20+ clouds, on-prem).
deepspeedai
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.