A note for the next session (lesson 7) thanks to @AdamF
There appear to be several issues in fastbook/clean/09_Tabular.ipynb that have been reported in the forum, but not in github issues. This issue aggregates them together.
I confirmed that all of them occur in the version included in the fastdotai/fastai-course docker image of 19-Nov-2020. I presume that the official docker image version of the course should run through cleanly without any errors.
- Some supporting modules are not installed: pip install kaggle waterfallcharts treeinterpreter dtreeviz (forum article)
- Downloading the kaggle file bluebook-for-bulldozers does not appear to work from python. There are multiple reports of this (including here) with the workaround being to download manually via the browser or via the commandline (kaggle competitions download -c bluebook-for-bulldozers).
- The code to download also fails because it tries to create a directory but needs a parents=True added to path.mkdir (see).
- The load/save pickle method should be changed to load_pickle/save_pickle (reported a couple of times on the forum including here)
- m_rmse(m, xs_filt2, y_filt), m_rmse(m2, valid_xs_time2, valid_y) raises an error. xs_filt2 should be xs_filt. as in m_rmse(m, xs_filt, y_filt), m_rmse(m2, valid_xs_time2, valid_y) (see here).
- procs_nn = [Categorify, FillMissing, Normalize] causes an error in the following line. The suggested work-around is to remove Normalize from the list (see here)
I haven’t tried running the notebooks yet but hopefully the above will help with debugging any issues you come across