Ecosyste.ms sponsors
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An open API service aggregating public data about GitHub Sponsors.
Principal Engineer at Red Hat | Project Lead @argoproj @kubeflow | Maintainer @tensorflow XGBoost | ML/AI Infrastructure | Author | Speaker | Technical Advisor
Funding Links: https://github.com/sponsors/terrytangyuan
Your support would be really appreciated and would encourage my on-going involvements in the open source community! Follow my Twitter, LinkedIn, Mastodon, and GitHub for updates!
🔔 You can schedule time with me to discuss open source and collaboration opportunities.
🔥 Check out my new book Distributed Machine Learning Patterns from Manning Publications!
What projects am I working on?
I am a maintainer/committer of the following projects:
Argo: project lead of the Argo Workflows and maintainer of Argo CD. Check out awesome-argo.
Kubeflow: Kubeflow Steering Committee member, project lead and co-chair of training operators. Check out awesome-kubeflow.
KServe: Standardized serverless ML inference platform on Kubernetes.
TensorFlow: co-author of TensorFlow Estimators and maintainer of TensorFlow I/O; recipient of Google Open Source Peer Bonus in 2016 for my contributions to TensorFlow.
XGBoost: maintainer of the Python and R packages.
Apache MXNet: co-author of the Scala package.
Couler: designed the unified interface and contributed to many major components of the system.
ElasticDL: designed and implemented several major components of the system.
In the meantime, I (co-)authored the following projects in areas of machine learning, data visualization, and tools: TensorFlow in R, metric-learn, ggfortify, reticulate, etc.
There are also other projects that I have made non-trivial contributions to as I come across areas of improvements, namely KServe, H2O, SQLFlow, pandas, SynapseML, etc. Please visit my projects page and GitHub page for more details.
What else am I involved in besides writing code?
Technical advisor, leadership, mentor at various companies and open source organizations.
Speaker at various conferences.
Co-author of three books: Distributed Machine Learning Patterns, TensorFlow in Practice, and Dive into Deep Learning (with TensorFlow).
Write blogposts related to open source technologies and sometimes share my thoughts via media interviews to broader audience.
How would your sponsorship support my work?
Your sponsorship will contribute directly to cover necessary expenses for developing, maintaining, and growing the projects, which includes but are not limited to the following:
Continuous integration, cloud services, and computing resources for testing related changes.
Travel expenses for speaking at local meetups, universities, and conferences.
Domains and hosting services for project websites.
Licenses for various softwares that improve my work efficiency.
Workflow Engine for Kubernetes
Language: Go - Stars: 15116Standardized Serverless ML Inference Platform on Kubernetes
Language: Python - Stars: 3674An Open Source Machine Learning Framework for Everyone
Language: C++ - Stars: 186571Scalable, 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, Flink and DataFlow
Language: C++ - Stars: 26354Distributed ML Training and Fine-Tuning on Kubernetes
Language: Go - Stars: 1622Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo
Language: Python - Stars: 390