Weekish notes

I’ve recently switched back from Sourdough yeast to dried packet yeast mix, given a recipe by a colleague (thanks Nick!). I immediately set to work modifying his recipe (well, cutting out steps if we’re honest). The first loaf looked fine but was bland – I cut out too much salt. The next was really very good (“shop quality”). For the third I used off-boil water for my autolyse and I think the water was still too hot and killed some of the yeast later giving me this dense lump. Later that evening after 2.5 hours I had a luke-warm water repeat loaf and it was brilliant. I confirmed this with toast & jam this morning.

I’ve got quite a log of notes for my two main recipes now and will have a Sourdough on the go again this weekend.

Working with my “still secret” client in a safe haven locked down remote instance I lack most of my usual tools (part by design, part my ignorance during configuration). I’ve got Vi so I’m getting my hands dirty with the underlying operations (hey! :bnext and :e work fine! Ctrl P does some sort of autocomplete! :ls lists my buffers!). This is a little painful and Apache Guacamole’s remote viewer can be troublesome (stripping £ symbols, giving me 3 different keyboard configs depending on when I login, forgetting some of my windows!) but on the whole the setup is working well.

I’ve also had to get down and dirty with Git – no GitK or other fun tools. I’ve discovered some nice light git configs like “git logline” which help with terminal based navigation in our small team.

Training classes are now listed for:

  • Software Engineering for Data Scientists (September) – write strong, tested, reliable and defensible code from Notebooks to modules to improve collaboration and resilience
  • Higher Performance Python (October) – profile CPU & memory usage, speed up your code, compile where useful and improve your Pandas & Dask to enable faster iteration and faster processing on your projects with minimal effort on your part
  • Successful Data Science Projects (November) – discover new process & tools to design data science projects that’ll run successfully, improve collaboration between your team and the wider business (this is built out of 15 years of painful lessons so you don’t have to make the same mistakes!)

Ian is a Chief Interim Data Scientist via his Mor Consulting. Sign-up for Data Science tutorials in London and to hear about his data science thoughts and jobs. He lives in London, is walked by his high energy Springer Spaniel and is a consumer of fine coffees.