Last night Jake and I presented CassieQ (the distributed message queue on cassandra) at the seattle cassandra users meetup at the Expedia building in Bellevue. Thanks for everyone who came out and chatted with us, we certainly learned a lot and had some great conversations regarding potential optimizations to include in CassieQ.
A couple good points that came up where how to minimize the use of compare and set with the monoton provider, whether we can move to time UUID’s for “auto” incrementing monotons. Another interesting tidbit was the discussion of using potential time based compaction strategies that are being discussed that could give a big boost given the workflow cassieq has.
But my favorite was the suggestion that we create “kafka” mode and move the logic of storing pointer offsets out of cassieq and onto the client, in which case we could get enormous gains since we no longer … Read more
A few weeks ago we had our second DC F# meetup with speaker Phil Trelford where he led a hands on session introducing decision trees. The goal of meetup was to see how good of a predictor we could make of who would live and die on the titanic. Kaggle has an excellent data set that shows age, sex, ticket price, cabin number, class, and a bunch of other useful features describing Titanic passengers.
Phil followed Mathias‘ format and had an excellent .fsx script that walked everyone through it. I think the best predictor that someone made was close to 84%, though it was surprisingly difficult to exceed that in the short period of time that we had to work on it. I’d implemented my own shannon entropy based ID3 decision tree in C# so this wasn’t my first foray into decision tree’s, but the compactness of the tree … Read more
Recently I organized an F# meetup in DC, and for our first event we brought in a wonderful speaker (Mathias Brandewinder) who’s topic was called: “Coding Dojo: a gentle introduction to Machine Learning with F#“.
I was certainly a little nervous about our first meetup, but a ton of great people came out: from experienced F# users, to people who had used other functional languages (like OCaml), to people with no functional experience. The goal of the meetup was to write a k-nearest neighbors classifier for a previously posted kaggle exercise to classify pixellated numbers.
Mathias did a great job of breaking people up into groups and then explaining what is machine learning and the criteria of the project in a surprsingly short time period. I think people were a little scared of jumping in since he only talked for about 10 to 15 … Read more
As you may have figured out, I like F# and I like functional languages. At some point I tweeted to the f# community lamenting that there was a dearth of F# meetups in the DC area. Lo and behold, tons of people replied saying they’d be interested in forming one, and some notable speakers piped up and said they’d come and speak if I set something up.
So, If any of my readers live in the DC metro area, I’m organizing an F# meetup featuring Mathias Brandewinder. We’ll be doing a hands on F# and machine learning coding dojo which should be a whole buttload of fun. Here’s the official blurb:
Machine Learning is the art of writing programs that get better at performing a task as they gain experience, without being explicitly programmed to do so. Feed your program more data, and it will get smarter at handling