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Materials for "Bayesian Methods for Machine Learning" Coursera MOOC

Home Page: https://www.coursera.org/learn/bayesian-methods-in-machine-learning

Jupyter Notebook 95.60% Python 4.40%

bayesian-methods-for-ml's Introduction

Bayesian Methods for Machine Learning course resources

https://www.coursera.org/learn/bayesian-methods-in-machine-learning

Wellcome to our GitHub repo for the course. You can clone the repository and solve the assignments locally, or run them on Google Colab.

Running on Google Colab

Google has released its own flavour of Jupyter called Colab, which has free GPUs!

Here's how you can use it:

  1. Open https://colab.research.google.com, click Sign in in the upper right corner, use your Google credentials to sign in.
  2. Click GITHUB tab, paste https://github.com/hse-aml/bayesian-methods-for-ml and press Enter
  3. Choose the notebook you want to open, e.g. week2/em_assignment.ipynb
  4. Click File -> Save a copy in Drive... to save your progress in Google Drive
  5. To use GPU click Runtime -> Change runtime type and select GPU in Hardware accelerator box
  6. If you run many notebooks on Colab, they can continue to eat up memory, you can check GPU memory usage with ! nvidia-smi.

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