lor_deck_statistics
bambi
| lor_deck_statistics | bambi | |
|---|---|---|
| 1 | 5 | |
| 0 | 1,019 | |
| - | 1.7% | |
| 0.0 | 8.0 | |
| almost 3 years ago | 5 days ago | |
| Python | Python | |
| - | MIT License |
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.
lor_deck_statistics
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MegaMogwai deck statistics
Sources: - Source code : https://github.com/TheRaphael0000/lor_deck_statistics - YouTube playlist used : https://www.youtube.com/playlist?list=PL_NQ1VZHmIfY5g0CPrJEEQ213nw2wdsSw
bambi
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Bayesian Structural Equation Modeling using blavaan
It is much less challenging with Bambi[1] and brms[2].
[1] https://bambinos.github.io/bambi/ -
Ask HN: What Are You Learning?
I’m trying to learn statistics. I’m up to implementing regressions in python using sci-kit learn.
I was playing around with Bayesian modelling last night with https://bambinos.github.io/bambi/ But I’m not really sure how to interpret the outputs.
Always open to reading about learning resources/books/videos/courses from others.
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how can I build a regression model which is penalised for moving away from an assumed set of coefficients?
I would suggest using Python's bambi; it is based on PyMC and it is very straightforward to use. We simply define our priors argument as a dictionary (quite literally: my_priors = {"feature_1": bmb.Prior("Normal", mu=4, sigma=4), "feature_n": bmb.Prior("Normal", mu=0.4, sigma=0.4)}) when creating our Bambi Model object and we are ready to go. They have a lot of worked exampling in their website.
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Which not so well known Python packages do you like to use on a regular basis and why?
For those interested in Bayesian modeling in Python we also have Bambi https://github.com/bambinos/bambi
- Release Bambi 0.6.0 · bambinos/bambi
What are some alternatives?
deffcode - A cross-platform High-performance FFmpeg based Real-time Video Frames Decoder in Pure Python 🎞️⚡
brms - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
mistletoe - A fast, extensible and spec-compliant Markdown parser in pure Python.
vimtk - A vim toolkit focused on gvim, IPython, and the terminal.
pyroute2 - Python Netlink and PF_ROUTE library — network configuration and monitoring
static-frame - Immutable and statically-typeable DataFrames with runtime type and data validation
auto-editor - Auto-Editor: Effort free video editing!
openapi-generator - OpenAPI Generator allows generation of API client libraries (SDK generation), server stubs, documentation and configuration automatically given an OpenAPI Spec (v2, v3)
aiosql - Simple SQL in Python
pydantic-to-typescript - CLI Tool for converting pydantic models into typescript definitions
rubygems - Library packaging and distribution for Ruby.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python