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Merge pull request #2 from ericmjl/readme-update
updated README
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# bayesian-stats-modelling-tutorial
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How to do Bayesian statistical modelling using numpy and PyMC3
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# getting started
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To get started, first identify whether you
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1. Prefer to use the `conda` package manager (which ships with the Anaconda distribution of Python), or if you
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2. prefer to use `pipenv`, which is a package authored by Kenneth Reitz for package management with `pip` and `virtualenv`, or if you
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3. Do not want to mess around with dev-ops.
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## `conda` users
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If this is the first time you're setting up your compute environment, use the `conda` package manager to **install all the necessary packages** from the provided `environment.yml` file.
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```bash
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conda env create -f environment.yml
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```
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To **activate the environment**, use the `conda activate` command.
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```bash
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conda activate bayesian-stats-modelling
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```
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**If you get an error activating the environment**, use the older `source activate` command.
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```bash
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source activate bayesian-stats-modelling
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```
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To **update the environment** based on the `environment.yml` specification file, use the `conda update` command.
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```bash
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conda env update -f environment.yml
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```
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## `pipenv` users
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Instructions are coming.
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## don't want to mess with dev-ops
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If you don't want to mess around with dev-ops, click the following badge to get a Binder session on which you can compute and write code.
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[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/ericmjl/bayesian-stats-modelling-tutorial/master)
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# data credits
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