Hacker News
- 2018's Top Python and R Packages for Data Science and AI https://heartbeat.fritz.ai/top-7-libraries-and-packages-of-the-year-for-data-science-and-ai-python-r-6b7cca2bf000 2 comments
Linked pages
- Bokeh documentation — Bokeh 2.4.3 Documentation http://bokeh.pydata.org/en/latest/ 66 comments
- GitHub - mwouts/jupytext: Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts https://github.com/mwouts/jupytext 41 comments
- spaCy · Industrial-strength Natural Language Processing in Python https://spacy.io/ 29 comments
- The Comprehensive R Archive Network https://cran.r-project.org/ 27 comments
- GitHub - slundberg/shap: A game theoretic approach to explain the output of any machine learning model. https://github.com/slundberg/shap 20 comments
- Medium https://medium.com/m/signin?isDraft=1&operation=login&redirect=https%3A%2F%2Fmedium.com%2F%40jamie_34747%2F79d382edf22b%3Fsource%3D 19 comments
- sparklyr http://spark.rstudio.com/ 10 comments
- Apache Spark™ - Unified Engine for large-scale data analytics http://spark.apache.org/ 9 comments
- GitHub - ropensci/drake: An R-focused pipeline toolkit for reproducibility and high-performance computing https://github.com/ropensci/drake 5 comments
- Comet ML - Build better models faster https://www.comet.ml/ 4 comments
- A general vectorised if-else — case_when • dplyr https://dplyr.tidyverse.org/reference/case_when.html 4 comments
- Automate Data Exploration and Treatment • DataExplorer https://boxuancui.github.io/DataExplorer/ 1 comment
- GitHub - EpistasisLab/tpot: A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. https://github.com/EpistasisLab/tpot 0 comments
- Interpreting Machine Learning Models: An Overview - KDnuggets https://www.kdnuggets.com/2017/11/interpreting-machine-learning-models-overview.html 0 comments
- GitHub - tensorflow/adanet: Fast and flexible AutoML with learning guarantees. https://github.com/tensorflow/adanet 0 comments
- Toward Reproducibility: Balancing Privacy and Publication | by Zach Scott | Towards Data Science http://towardsdatascience.com/toward-reproducibility-balancing-privacy-and-publication-77fee2366eee 0 comments
- https://hioptimus.com/ 0 comments
- GitHub - hi-primus/optimus: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark https://github.com/ironmussa/Optimus 0 comments
- GitHub - ModelOriented/DALEX: moDel Agnostic Language for Exploration and eXplanation https://github.com/pbiecek/DALEX 0 comments
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