Hacker News
- See the future with Adaptive Machine Learning https://www.appliedexploration.com/p/back-to-the-future-with-time-series 2 comments
- We ended up building a Time-Series Cross-Validation library from scratch https://www.appliedexploration.com/p/back-to-the-future-with-time-series 5 comments
- Back to the Future with Time-Series Cross-Validation https://www.appliedexploration.com/p/back-to-the-future-with-time-series 3 comments machinelearningnews
Linking pages
Linked pages
- GitHub - Nixtla/statsforecast: Lightning ⚡️ fast forecasting with statistical and econometric models. https://github.com/Nixtla/statsforecast 22 comments
- GitHub - 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 https://github.com/dmlc/xgboost 0 comments
- GitHub - dream-faster/fold: 🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. https://github.com/dream-faster/fold 0 comments
- GitHub - dream-faster/krisi: ⏳ Evaluation of Time-Series Predictions with powerful pdf and web Reporting. Tailored for evaluation of metrics over time! https://github.com/dream-faster/krisi 0 comments
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