arviz
NumPy
| arviz | NumPy | |
|---|---|---|
| 3 | 278 | |
| 1,548 | 26,774 | |
| 1.2% | 1.5% | |
| 7.7 | 10.0 | |
| 5 days ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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arviz
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Matplotlib for sabermetric analysis
pymc3 is the standard Python library for Bayesian statistics, and used ArviZ for plotting, built on top of matplotlib
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What is Probabilistic Programming?
This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing
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Hacktoberfest: 69 Beginner-Friendly Projects You Can Contribute To
https://github.com/arviz-devs/arviz Exploratory analysis of Bayesian models with Python
NumPy
- NumPy 2.0.0
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Documenting my pin collection with Segment Anything: Part 3
NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations.
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Awesome List
NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation.
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NumPy for Beginners: A Basic Guide to Get You Started
This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples.
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2 Minutes to JupyterLab Notebook on Docker Desktop
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it.
- Taming Floating-Point Sums
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
What are some alternatives?
matplotlib - matplotlib: plotting with Python
SymPy - A computer algebra system written in pure Python
Babel (Formerly 6to5) - 🐠 Babel is a compiler for writing next generation JavaScript.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
seaborn - Statistical data visualization in Python
SciPy - SciPy library main repository
PyMC - Bayesian Modeling and Probabilistic Programming in Python
blaze - NumPy and Pandas interface to Big Data
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.
Numba - NumPy aware dynamic Python compiler using LLVM
probability - Probabilistic reasoning and statistical analysis in TensorFlow
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).