Bayesian Modeling and Computation in Python

Last update: Jan 02, 2023

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Overview

Bayesian Modeling and Computation in Python

Open access and Code

This repository contains the open access version of the text and the code examples in the book. All of this can be more easily viewed at www.bayesiancomputationbook.com

See a mistake?

If you see any issues please create an issue on the issue tracker

Environment installation

To run the code you will need to install the correct packages in a computational environment. We have provided instructions below for common options.

Conda

conda env create -f environment.yml
conda activate bmcp

Colab

The book code can also be run using Google Colab. https://colab.research.google.com

More instructions to come soon

Owner

Bayesian Modeling and Computation in Python

Code, references and all material to accompany the text

GitHub Repository https://www.bayesiancomputationbook.com

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Bayesian Modeling and Computation in Python

Related tags

Overview

Bayesian Modeling and Computation in Python

Open access and Code

See a mistake?

Environment installation

Conda

Colab

Owner

Bayesian Modeling and Computation in Python

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

Sequence learning toolkit for Python

Forecast dynamically at scale with this unique package. pip install scalecast

Book Recommender System Using Sci-kit learn N-neighbours

Banpei is a Python package of the anomaly detection.

Continuously evaluated, functional, incremental, time-series forecasting

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

Fourier-Bayesian estimation of stochastic volatility models

To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction

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STUMPY is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks

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