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RT : At our tonight in , made it rain with . Join our vibrant meetup c…
H2O  NewJersey  meetup  DriverlessAI  from twitter_favs
7 weeks ago by neuralmarket
Keeping the Big Picture In Sight at H2O World
These are ideas that shaped Ambati’s path. “I chose to build a machine learning library 10 years ago on the streets of San Francisco, and before you know it, there’s hundreds of people using it, thousands of people,” Ambati said. “To connect the dots, from individual to universal, takes an action — just one click.”
H2O  H2OWorld  DataScience 
10 weeks ago by neuralmarket
interpretable_machine_learning_with_python/xgboost_pdp_ice.ipynb at master · jphall663/interpretable_machine_learning_with_python
A key to building interpretable models is to limit their complexity. The more complex a model is, the harder it is to explain and understand. Overly complex models can also make unstable predictions on new data, which is both difficult to explain and makes models harder to trust. Monotonicity constraints not only simplify models, but do so in a way that is somewhat natural for human reasoning, increasing the transparency of predictive models. Under monotonicity constraints, model predictions can only increase or only decrease as an input variable value increases, and the direction of the constraint is typically specified by the user for logical reasons. For instance, a model might be constrained to produce only increasing probabilities of a certain medical condition as a patient's age increases, or to make only increasing predictions for home prices as a home's square footage increases.
Python3  H2O  MachineLearning-interpretability 
january 2019 by neuralmarket
novyden: Finally, You Can Plot H2O Decision Trees in R
Creating and plotting decision trees (like one below) for the models created in H2O will be main objective of this post:
MachineLearning  H2O  RStats 
december 2018 by neuralmarket
RT : Yet another new feature in - a new tree API for inspecting tree-based models. giving an…
H2O  from twitter
december 2018 by neuralmarket
RT : High Performance with Integrations Meetup in on Nov 20. from…
KNIME  H2O  Berlin  MachineLearning  from twitter_favs
october 2018 by neuralmarket
(429) https://twitter.com/i/web/status/1040646046324547586
Know a middle schooler interested in learning more about ? Check out and next on 9/29, 1…
H2O  AI  Meetup  from twitter_favs
september 2018 by neuralmarket
Benchmarking Random Forest Implementations | Data Science Los Angeles
I currently have the need for machine learning tools that can deal with observations of the order of 10 millions in the context of binary classification. That kind of data is a few GBs in size and it fits comfortably nowadays in the RAM of a decent single machine. It is a trivial task for linear models, as there are
randomforest  Brandon_Loudermilk__Ph.D.  Data_Science__Machine_Learning__and_NLP  forest  h2o  Kifi  python  random  scikit 
august 2018 by ohnice
h2o/daemons-cc: FreeBSD's congestion controller
FreeBSD の輻輳制御コードをライブラリ化するらしい。
h2o  freebsd  c 
june 2018 by summerwind

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