Bayesian-Statistics-Econometrics VS edward2

Compare Bayesian-Statistics-Econometrics vs edward2 and see what are their differences.

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Bayesian-Statistics-Econometrics edward2
1 1
71 667
- 1.3%
10.0 6.4
over 1 year ago 8 days ago
Jupyter Notebook Jupyter Notebook
MIT License Apache License 2.0
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Bayesian-Statistics-Econometrics

Posts with mentions or reviews of Bayesian-Statistics-Econometrics. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-24.
  • Python for Econometrics for Practitioners [Free Online Courses]
    5 projects | /r/CompSocial | 24 Aug 2023
    Bayesian Statistics with Python: Bayesian statistics is the last pillar of quantitative framework, also the most challenging subject. The course will explore the algorithms of Markov chain Monte Carlo (MCMC), specifically Metropolis-Hastings, Gibbs Sampler and etc., we will build up our own toy model from crude Python functions. In the meanwhile, we will cover the PyMC3, which is a library for probabilistic programming specializing in Bayesian statistics.

edward2

Posts with mentions or reviews of edward2. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Bayesian-Statistics-Econometrics and edward2 you can also consider the following projects:

Linear-Algebra-With-Python - Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.

Knet.jl - Koç University deep learning framework.

Basic-Statistics-With-Python - Introduction to statistics featuring Python. This series of lecture notes aim to walk you through all basic concepts of statistics, such as descriptive statistics, parameter estimations, hypothesis testing, ANOVA and etc. All codes are straightforward to understand.

conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

Econometrics-With-Python - Tutorials of econometrics featuring Python programming. This is a crash course for reviewing the most important concepts and techniques of basic econometrics, the theories are presented lightly without hustles of derivation and Python codes are straightforward.

uncertainty-baselines - High-quality implementations of standard and SOTA methods on a variety of tasks.

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 ;)

probability - Probabilistic reasoning and statistical analysis in TensorFlow

Time-Series-and-Financial-Engineering-With-Python - A series of lessons on time series analysis with Python

cracking-the-data-science-interview - A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.

geomstats - Computations and statistics on manifolds with geometric structures.