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The goal of this tutorial is to present Blind Source Separation (BSS) problems and the main methods to solve them. This tutorial does not provide in-depth mathematical explanations for every methods; the emphasis is rather on illustrations and intuition.
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7.**[Introduction to MCMC and Bayesian inference](https://colab.research.google.com/drive/1EUF7-CwamhAT6wedntStdb4x3dDbihoo?usp=sharing)** | [](https://www.youtube.com/watch?v=EfWEGBHeA3k)[](https://colab.research.google.com/drive/1EUF7-CwamhAT6wedntStdb4x3dDbihoo?usp=sharing)
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8.**[Introduction to MCMC and Bayesian inference](https://colab.research.google.com/drive/1EUF7-CwamhAT6wedntStdb4x3dDbihoo?usp=sharing)** | [](https://www.youtube.com/watch?v=EfWEGBHeA3k)[](https://colab.research.google.com/drive/1EUF7-CwamhAT6wedntStdb4x3dDbihoo?usp=sharing)
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*Authors:*[@EiffL](https://github.com/EiffL)
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This tutorial is a practical introduction to Bayesian inference using emcee and
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touching on questions related to measurement errors and covariance.
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9.**[Brief tutorial on importance sampling](https://github.com/CosmoStat/Tutorials/tree/is)** | [](https://github.com/CosmoStat/Tutorials/tree/is)
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