Welcome to your guide on diving into the world of Bayesian statistics with the help of Python and PyMC3. This article will guide you through installing the necessary tools, accessing the resources, and troubleshooting common issues you may encounter along the way.

Introduction to Bayesian Statistics

Before we jump into the specifics, let’s understand what Bayesian statistics is. Imagine you are a detective trying to solve a case. You gather evidence (data) and update your beliefs (prior probabilities) as new data comes in, refining your understanding of the case. This is the essence of Bayesian thinking, and the book Statistical Rethinking provides a clear guide on how to approach this statistical method.

Repository Update

This repository has been deprecated in favour of this new repository. Please check that repository for updates, issue tracking, and pull requests.

Getting Started

To kick off your journey, you will want to set up your environment correctly to run the provided Jupyter notebooks. Here’s how you can do this:

Step 1: Install Anaconda

First, download and install Anaconda, which is a package manager that will help you effortlessly handle your Python packages and environments.

Step 2: Install Required Dependencies

Once Anaconda is set up, navigate to the directory where you have the project files and run the following command:

conda env create -f environment.yml

This command will create an isolated environment with all necessary dependencies installed.

Step 3: Activate Environment

Activate your newly created environment by running:

source activate stat-rethink-pymc3

You are now ready to explore Bayesian statistics with the examples provided!

Viewing the Notebooks

You can access the Jupyter notebooks for practical examples through nbviewer.

Troubleshooting Common Issues

• Issue: Unable to activate the environment.
• Solution: Ensure you are in the correct terminal and the Anaconda installation was successful. Re-check your path settings.
• Issue: Packages not found after the installation.
• Solution: Review the environment.yml file for package listings. If some packages are missing, install them individually using conda install package_name.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Contributing to the Project

If you wish to contribute to the project, your input is welcome! You can send in your pull requests to this repository.

Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.