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Fix broken links in README
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README.rst

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@@ -10,7 +10,7 @@ focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (
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algorithms. Its flexibility and extensibility make it applicable to a
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large suite of problems.
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Check out the `getting started guide <http://docs.pymc.io/notebooks/getting_started>`__, or
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Check out the `getting started guide <https://docs.pymc.io/en/stable/pymc-examples/examples/getting_started.html>`__, or
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`interact with live examples <https://mybinder.org/v2/gh/pymc-devs/pymc/main?filepath=%2Fdocs%2Fsource%2Fnotebooks>`__
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using Binder!
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For questions on PyMC, head on over to our `PyMC Discourse <https://discourse.pymc.io/>`__ forum.
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If you already know about Bayesian statistics:
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- `API quickstart guide <http://docs.pymc.io/notebooks/api_quickstart>`__
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- The `PyMC tutorial <http://docs.pymc.io/notebooks/getting_started>`__
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- `PyMC examples <https://docs.pymc.io/nb_examples/index.html>`__ and the `API reference <http://docs.pymc.io/api>`__
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- `API quickstart guide <https://docs.pymc.io/en/stable/pymc-examples/examples/pymc3_howto/api_quickstart.html>`__
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- The `PyMC tutorial <https://docs.pymc.io/en/stable/pymc-examples/examples/getting_started.html>`__
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- `PyMC examples <https://docs.pymc.io/nb_examples/index.html>`__ and the `API reference <https://docs.pymc.io/en/stable/api.html>`__
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Learn Bayesian statistics with a book together with PyMC:
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---------------------------------------------------------

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