stat_rethinking_2022
Statistical Rethinking course winter 2022 (by rmcelreath)
stat_rethinking_2020
Statistical Rethinking Course Winter 2020/2021 (by rmcelreath)
| stat_rethinking_2022 | stat_rethinking_2020 | |
|---|---|---|
| 13 | 8 | |
| 4,112 | 656 | |
| - | - | |
| 1.8 | 2.6 | |
| almost 3 years ago | almost 4 years ago | |
| R | R | |
| - | - |
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_2020
Posts with mentions or reviews of stat_rethinking_2020.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-05-07.
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[Q] Book on Bayesian statistics?
Bayesian rethinking is quite a good book and has been translated to Python.
- [E] Statistical Rethinking 2022 by Richard McElreath
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I have a small sample size time series with potentially lagged predictor values which are also time series. What could be potential methods to analyse these data?
If you want a full course on Bayesian Multilevel models, there's the excellent "statistical rethinking": lectures/content here and code here
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How to incorporate Bayes Inference into inplay betting model using R?
If you're unfamiliar with Bayesian analysis, I recommend reading Richard McElreath's Statistical Rethinking. It has associated R exercises and a lectures (found here)
- Any good video series for learning Bayesian stats?
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Quantitative Methods Course
A wonderful introductory course from a Bayesian point of view: https://github.com/rmcelreath/stat_rethinking_2020
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Any resource suggestion for 6420 Bayesian Statistics?
https://github.com/rmcelreath/stat_rethinking_2020 includes slides and videos.
What are some alternatives?
When comparing stat_rethinking_2022 and stat_rethinking_2020 you can also consider the following projects:
botorch - Bayesian optimization in PyTorch
brms - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
interpretable-ml-book - Book about interpretable machine learning
stan - Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
stat_rethinking_2023 - Statistical Rethinking Course for Jan-Mar 2023
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers - aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
pymc-resources - PyMC educational resources
noisy-bayesian-optimization - Bayesian Optimization for very Noisy functions
stat_rethinking_2022 vs botorch
stat_rethinking_2020 vs brms
stat_rethinking_2022 vs interpretable-ml-book
stat_rethinking_2020 vs stan
stat_rethinking_2022 vs stat_rethinking_2023
stat_rethinking_2020 vs Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
stat_rethinking_2022 vs pymc-resources
stat_rethinking_2022 vs noisy-bayesian-optimization