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https://github.com/PNNL-PREMIS/SULI/issues/1
http://swcarpentry.github.io/r-novice-inflammation/
http://swcarpentry.github.io/r-novice-inflammation/01-starting-with-data/index.html
https://swir…
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@royklaassebos
objective: complete novices should be able to familiarize themselves with R
scope: this is a basic course for anybody from the marketing management or marketing analytics programs…
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** types. of algorithms.
1. Linear discriminant analysis
2. Regression
3. Naive Bayes
4. Support vector machines
5. Classification and regression trees
6. Random forests
7. Boosting
etc.
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I saw an [article](http://www.computerworld.com/article/2497464/business-intelligence/business-intelligence-60-r-resources-to-improve-your-data-skills.html) yesterday with various resources for R. I l…
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Hello folks,
I parsed all issues here and although we keep talking about data science, I didn't find proposals for machine learning either using R or Python.
Who is willing to co-start a series of m…
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# posit::conf(2024) – Fonti Kar
If you told me 15 years ago when I was learning how to program in R that I would be attending posit::conf(2024) - a 3 day conference that celebrates data science and i…
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Hey,
is there a way to set layer Specific Learning Rate for the R version?
I found two different posts, one naming: Optimizer.set_lr_scale(). and one mx.sym.YOURSYMBOL(attr={'lr_mult': 0.01}).
…
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Is there an example or packages for deep reinforcement learning written in MXNet R?
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Might pdp be extended to work directly with output from Keras3? Also, variable importance plots would be a nice addition. There are number of related ideas in Molnar’s nice survey book “Interpretable …
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In the documentation the causal learning depends on an external library CDT:
- https://github.com/py-why/dowhy/blob/main/docs/source/example_notebooks/dowhy_causal_discovery_example.ipynb
- https:…