Our fourth Un-hackathon took on a new structure. Adding to the programme of hands-on, project style skillsharing and development over a day of focused hacking, organisers arranged talks from industry leaders and accomplished practitioners.
About 40 people came to hear the talks and join the traditional hackathon groups which we go into detail about in separate posts, linked below. For more detailed writing on each project’s challenges and achievements, scroll past the talks section.
Lavine Hemlani and Bilal Khan from Accelerated HK began the talks with an inspiring speech on the future of artificial intelligence. Khan posed this call to action: “Do we let AI be in the hands of very few people?” We don’t, and the pair told us their strategy to teach AI and grow a community of practitioners so that this emerging power is not just a tool for big business.
Robert Porsch PhD. spoke on genomics — the mapping and study of the genome — and the problems he was facing in dealing with 80-90 gigabyte genome data sets. His work on human genomes involves seeking out unique DNA patterns of complex illnesses, sometimes hidden in chains of thousands of mutations — in order to identify them and predict the genetic causes of diseases such as huntington’s or the risk of developing cancer.
Gogovan’s Michal Szczecinski — Hong Kong’s first unicorn company — took us through his role in predicting demand and spotting fraud in his business. By constructing visualisations and dashboards, his business can work with greater oversight. As he says, his role is “to facilitate a smarter decision”. He shared his six steps to general optimisation: learn, brainstorm, prioritise, develop, execute, analyse, and showed us a methodically produced manual on practicing data science.
Ho Wa Wong, an open data activist, has been reconstructing government data into structured datasets which the Hong Kong government hasn’t yet made publicly usable in a convenient way. The data.gov.hk site has public government data but it’s limited both in historical data and range, and the date is often in various formats. Wong aims to add to the pool of available data by coding systems to scrape and clean the data and make the sets available here. He also parsed the Legco transcript and made it available here.
Similarly on a public focused level, Data Science Hong Kong organiser Wang Xiaozhou has been using a hidden Markov model in an attempt to improve geocoding in Hong Kong. The model is being trained to spot the particles of addresses and as Wang showed, by training the model to identify parts of the address such as street types or the district name the model can learn fast and develop speed after few steps, even when the format of the address is changing.
From the academic sector, Leif Sigerson has been mining the Twitter API to find dialogues from small communities talking about psychological problems. Using R and rtweet he would scrape sets of up to 3200 tweets from identified users to build an “ego map”, which connects dots between a user and their followers, and then aims to map out the connectedness of their followers to each other. The psychology department at his university was excited by the prospect of a large sample size but he said it was still sceptical about the methodologies employed in his approach.
Jason Chan Jin-an had built a predictor of MMA match outcomes which he said had more than 70 per cent accuracy by comparing fighters on factors like their winning record and physical attributes, and his model was indeed earning him some money, he said. Jason came to the un-hackathon to enhance his predictor by automatically setting fighters status to active or retired, thereby avoiding comparisons between active and non-active fighters.
See more about his project here.
Xavier Mathieu, a Data Science Hong Kong organiser and former quantitative team manager at BNP Paribas conducted talks on how to study cryptocurrencies and develop low- and high-frequency trading strategies as well as identifying manipulation and seeing opportunities in them.
See more about his project here.