stat_rethinking_2022
Statistical Rethinking course winter 2022 (by rmcelreath)
stat_rethinking_2023
Statistical Rethinking Course for Jan-Mar 2023 (by rmcelreath)
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| stat_rethinking_2022 | stat_rethinking_2023 | |
|---|---|---|
| 13 | 6 | |
| 4,101 | 2,130 | |
| - | - | |
| 1.8 | 4.0 | |
| about 2 years ago | 5 months ago | |
| R | R | |
| - | Creative Commons Zero v1.0 Universal |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
stat_rethinking_2022
Posts with mentions or reviews of stat_rethinking_2022.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-05.
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Is there another way to determine the effect of the features other than the inbuilt features importance and SHAP values? [Research] [Discussion]
I would recommend the lectures and book of Statistics Rethinking: https://github.com/rmcelreath/stat_rethinking_2022
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[Q] How is multilevel modelling different from a simple interaction/ moderation term?
Not a direct answer to your question, but I'd highly recommend Richard McElreath's lectures and book for learning multilevel modelling.
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Resources for learning Bayesian stats
Statistical Rethinking is an awesome Bayesian introductory course for people that already know some statistical modeling (i.e. GLM, HLM, ...) from the frequentist side.
- Boss wants me to model a process and tweak the parameters to minimize the response variable. How can I do that? e.g. number of customers waiting in a bank.
- Short Course on Statistics for Lab Scientists?
- Minimální znalost statistiky pro junior Data Scientist / Engineer pozici (ve finančnim sektoru)?
- Need a data set that I can do linear regression on but also apply hierarchical modelling via Bayesian methods.
- Statistical Rethinking (2022 Edition)
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How to be a biz/tech Anthropologist
Either way, try to pick up some computational and especially statistical expertise on the side. If you can't find coursework for it at your uni, I highly recommend McElreath's Statistical Rethinking. He recently started his lecture series for this year, with resources openly available: https://github.com/rmcelreath/stat_rethinking_2022
stat_rethinking_2023
Posts with mentions or reviews of stat_rethinking_2023.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-05.
- Statistical Rethinking Course for Jan-Mar 2023
- Statistical rethinking 2023 course archive
- Statistical Rethinking for 2023
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Is there another way to determine the effect of the features other than the inbuilt features importance and SHAP values? [Research] [Discussion]
The 2023 version is currently in process: https://github.com/rmcelreath/stat_rethinking_2023
- Statistical Rethinking (2023 Edition)
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[E] FYI: Statistical Rethinking (2023) by rmcelreath
The course will be about causal inference and Bayesian data analysis. You can find the course materials on GitHub - rmcelreath/stat_rethinking_2023: Statistical Rethinking Course for Jan-Mar 2023.
What are some alternatives?
When comparing stat_rethinking_2022 and stat_rethinking_2023 you can also consider the following projects:
stat_rethinking_2020 - Statistical Rethinking Course Winter 2020/2021
botorch - Bayesian optimization in PyTorch
interpretable-ml-book - Book about interpretable machine learning