Matt McKay

It depends on your hardware. Newer hardware has less overhead due to built-in virtualization support. But likely to vary between 2% and 10% by the look of it. http://serverfault.com/questions/135431/is-virtual-machine-slower-than-the-underlying-physical-machine Thanks...

Hi All, There are a few students who have reported not having full screen size. To get this to work properly it is best to install the virtual box add-on...

ENH: Basic generic theme - css, js, tpl

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This PR adds a basic theme for editing tasks.

FIX: remove unnecessary _static path in jupyter_static_path

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This PR removes an unecesary `_static` path. - [ ] requires `sphinxcontrib-jupyter=0.4.4` which has a release target of 13th September 2019

MAINT: Upgrade to anaconda=2024.02 and cuda=12.3.1

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This PR - [x] upgrades to `anaconda=2024.02` - [x] upgrades to `CUDA=12.3.1` this PR is part of https://github.com/QuantEcon/meta/issues/130 requires: #387 - [ ] this PR is waiting on `interpolations` to...

We will need to add sphinx-reredirect to the docker build environment - [ ] remove manual install step from `CI.yml`

Fix Long Run Time (bayes_nonconj)

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It is currently taking the cache almost 3 hours to run this lecture set (from scratch). There are a number of issues reported by tensor flow such as: ``` /__w/lecture-python.myst/lecture-python.myst/lectures/wealth_dynamics.md:...

Some lectures have deviated using `pmatrix` instead of `bmatrix`: https://manual.quantecon.org/writing/styleguide.html Such ashttps://python.quantecon.org/finite_markov.html and probably elsewhere. It would be great to regex across the lecture for `pmatrix` and update

For better compatibility with Google Colab we should - [ ] migrate back from `conda` to `pip` for installing additional packages - [x] The `jupyter notebook` based `contents` links don't...

[windows] Seems to be a unicode issue when compiling on Windows

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There appears to be a `unicode` issue when building these lectures on the `windows` platform, [cake_eating_numerical.log](https://github.com/QuantEcon/lecture-python.myst/files/6573554/cake_eating_numerical.log) [coleman_policy_iter.log](https://github.com/QuantEcon/lecture-python.myst/files/6573555/coleman_policy_iter.log) [egm_policy_iter.log](https://github.com/QuantEcon/lecture-python.myst/files/6573556/egm_policy_iter.log) [ifp.log](https://github.com/QuantEcon/lecture-python.myst/files/6573557/ifp.log) [markov_perf.log](https://github.com/QuantEcon/lecture-python.myst/files/6573558/markov_perf.log) [optgrowth_fast.log](https://github.com/QuantEcon/lecture-python.myst/files/6573559/optgrowth_fast.log) [optgrowth.log](https://github.com/QuantEcon/lecture-python.myst/files/6573560/optgrowth.log)