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xgboost.ai The new home for the XGBoost community :) Let us make better data science together
xgboost.ai XGBoost Scalable and flexible gradient boosting Latest posts 5
This is a solution that comes out from a lot our early lessons in building XGBoost, an open ABI foundation would definitely help to advance the ecosystem together
📢Excited to introduce Apache TVM FFI, an open ABI and FFI for ML systems, enabling compilers, libraries, DSLs, and frameworks to naturally interop with each other. Ship one library across pytorch, jax, cupy etc and runnable across python, c++, rust tvm.apache.org/2025/10/21/tvm…View quoted post on X
XGBoost 2.0 is here github.com/dmlc/xgboost/r…
github.com Releases · dmlc/xgboost 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, Flink and DataFlow - Releases... Checkout @tqchenml talking about the original story behind the creation of XGBoost, and followup ML compilation projects to bring LLM everywhere in the latest @latentspacepod
I had an enjoyable chat with @FanaHOVA and @swyx on machine learning systems and bringing high-performance universal deployment for ML models. Checkout the latest episode in latent space 👉View quoted post on X
Machine learning compilation is an emerging topic that everyone who cares about ML in the wild want to know.
A summer endeavor, developing MLC: the first open lecture series on ML compilation. Machine learning compilation is an emerging field for systematic optimization and deployment of AI workloads. Hope to share adventures and fun with the community mlc.ai/summer22/ 🚀View quoted post on X