stan
Elo-MMR
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| stan | Elo-MMR | |
|---|---|---|
| 44 | 4 | |
| 2,515 | 154 | |
| 0.8% | - | |
| 9.5 | 0.0 | |
| 11 days ago | 3 months ago | |
| C++ | C++ | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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stan
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Elevate Your Python Skills: Machine Learning Packages That Transformed My Journey as ML Engineer
Alternatives: stan and edward
- How often do you see Bayesian Statistics or Stan in the DS world? Essential skill or a nice to have?
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What do actual ML engineers think of ChatGPT?
I tend to be most impressed by tools and libraries. The stuff that has most impressed me in my time in ML is stuff like pytorch and Stan, tools that allow expression of a wide variety of statistical (and ML, DL models, if you believe there's a distinction) models and inference from those models. These are the things that have had the largest effect in my own work, not in the sense of just using these tools, but learning from their design and emulating what makes them successful.
- ChatGPT4 writes Stan code so I don’t have to
- Automatic differentiation in C
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[D] Programming language for developing computational statistics algorithms
I'd say take a look at Stan (https://mc-stan.org/)
Well it sounds a lot like you are listening to developers talk about coding languages they like for high performance compute. This is not what you want to be spending all your time doing afaik. The more appropriate languages to get into would be the classic Python and R. Julia if you dont give a shit about productionizing your code and https://mc-stan.org/ Stan if you are really locked into bayesian inference and wanted to pick julia anyway.
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Is python necessary to learn machine learning?
Even if RStudio & the Tidyverse have mostly been promoting a functional programming style in R, it has full support for OOP (see R6 or R7 for more modern implementations of it). Let's not even mention the excellent Stan ecosystem for Probabilistic programming / Bayesian modeling, or Bioconductor, the biggest repository of bioinformatics packages & tools of any language.
- [Q] Updated book or review paper on MCMC methods
- Stan in Nim?
Elo-MMR
We haven't tracked posts mentioning Elo-MMR yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
PyMC - Bayesian Modeling and Probabilistic Programming in Python
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
rstan - RStan, the R interface to Stan
brms - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
probability - Probabilistic reasoning and statistical analysis in TensorFlow
ZLUDA - CUDA on AMD GPUs
pyro - Deep universal probabilistic programming with Python and PyTorch
FlatBuffers - FlatBuffers: Memory Efficient Serialization Library
MultiBUGS - Multi-core BUGS for fast Bayesian inference of large hierarchical models
fastbaps - A fast approximation to a Dirichlet Process Mixture model (DPM) for clustering genetic data
rnim - A bridge between R and Nim
arviz - Exploratory analysis of Bayesian models with Python