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Weekly Update: Oct 11, 2018

I had detailed talks with two guys from my Statup School Group. They both gave me some Excel sheets they are interested in processing. I was able to write a script to do something potentially useful in both cases. I'm still in discussions with both of them to figure out where to go from here. I will probably reach out to a broader audience this week to see if I can identify a cluster of use-cases here.

I also spent some time looking into neural networks. A lot of research in the field of automatic coding type stuff appears to be focused there. Here are some articles I've been wading through:

There seems to be an enormous amount of knowledge required to understand the above studies to the point where I would be able to do useful work using similar approaches. It would be a big time investment to learn all that stuff. I'm not sure whether it would be worth it. Even if I did learn everything, the cutting edge doesn't quite seem sufficient to produce a marketable product. I will probably spend some time digging into it further though, despite my hesitations. I noticed there are some machine learning tutors reachable thorugh -- I'm thinking about hiring one of them to make the learning process more efficient.

I also did some random side work last week:

I added better search to my note taking tool, Electric Toothbrush. The motivation was that I had some notes about how to parse Excel spreadsheets in Python, but I couldn't find them -- because the note title was "read excel python" while my query was "parse excel python". I fixed this by basically switching from AND'ing together the terms in my search query to OR'ing them. This leads to better recall but lower precision. I needed to offset the precision loss in order to keep search working well which I did by basically incorporating inverse document frequency into the search results. So far the results seem to be a significant improvement.

Twice over the last couple of months I’ve found myself in a situation where I wrote a prototype of some idea in Python before realizing it would be better if the code was in Javascript. It would be cool if I had something that could automatically translate Python code to Javascript: I worked on this for about a day, but I think I will abandon the project since the cost/benefit ratio is too low to justify the time it would take to complete.

I have a tool that takes a screenshot of my desktop every five seconds ( and uploads them to S3. I can combine this with quantified-self tools like Task Ranger and Metal Detector to look more deeply into time periods of interest. I cleaned up the workflow for screenshot downloading and it's now working pretty well. In particular, querying for the screenshots from a remote EC2 machine and then downloading them to my local computer is much faster than trying to download them directly. This is because all of the millions of screenshots I have are in a single bucket and when you query for a particular subset S3 apparently does a linear scan through the entire bucket which somehow requires many separate http queries (something to do with pagination I assume).

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