Unhackathon #10 roundup

Our first unhackathon after Typhoon Mangkhut blew out our September meetup kicked off with a talk about a practical application of machine learning, and followed up with an introduction of the benefits of the L0 norm.

Two teams attempted to satisfy their curiosity with analysis of the Hong Kong housing market and a new cryptocurrency blockchain.

Our events happen monthly on Sundays, including talks from industry leaders and practitioners of data science, followed by a pitch session and group work on projects for the afternoon. You can find out more and stay up to date with our next events on our Slack channel, our Meetup page and on Facebook.

The talks

South China Morning Post data engineer Jonathan Barone introduced us to project Dali, a tool under development at the 115 year old newspaper intended to catalogue elements in images, potentially identifying faces and places from the media company’s archive of images.

You can see his talk in the video and slides below.

Dali slides can be read here.

Robert Porsch showed us an alternative way to regularise parameters by using the L0 (L-zero) norm.
He demonstrated that this new penalisation function is able to outperform more traditional approaches, such as the L1 norm, given a large enough sample size.
He has applied this method to predict the genetic risk for health outcomes and behavioural traits.

Read his slides here.

(Apologies for not including video, we had technical difficulties trying to record it.)

The hackathon session

Two groups formed to tackle real estate and create a new blockchain recommendation system.

Take a look at the videos of their presentations below.

Blockchain recommendation engine

This team set themselves the ambitious target of creating a system that can recommend a spread of cryptocurrencies using a number of existing systems including BigQuery, Docker and others. Check out the outcome in their presentation below.

Real estate analysis

This team started with the transaction history of real estate in Hong Kong and another dataset of stock exchange information. Their results were to show which areas had higher risk of low return on investment, also showing a correlation between stock market turmoil and housing transactions.

 

Next event

We are looking at dates in early December. Stay tuned on our Slack #events and Facebook for announcements.