Monthly un-hackathon + talks

Join our Data Science un-hackathon on the first Sunday every month. We host a full day of fun and working together on your data science projects!

At this event attendees will have the chance to pitch their projects, or join with others. We start the day with some fantastic industry specialists who will share their experiences operating in the data science field.

The event will be held at the South China Morning Post offices at Times Square on the first Sunday of the month.

Signup at: Eventbrite, Meetup, Facebook

Schedule of events:

9.30am – Arrive, registration
10am – Welcome
10.15am – Talks begin
11.30am – Pitch session, recruitment
12pm – Work on projects
5.30 pm – Present results of work session

Location:

SCMP: 20/f, Tower 1, Times Square, 1 Matheson St, Causeway Bay

Requirements:

Laptop / charger for those joining the coding
Prepared data, and projects pitches for the ones submitting projects
If presenting, send us your presentation slides ahead of time so we can prepare them.
HK$50 in cash for the space rental

Recommendations for project submissions:

Send us your presentation slides! Drop a link to one of the organisers on Slack or another way. We want to minimise time spent switching laptops so we will run your slides from our pc.
Prepare data in advance as much as you can; spending the day cleaning or retrieving data won’t gather crowds of DS! Contact organisers if you need a data repository to share data with all your team members.
If the project is already underway, prepare an introduction to it so that people can join. If you’re presenting slides, send them to us before you arrive, make sure the task you propose is feasible during the time of the event, and describe the skills you expect your team to have: R or Python? AWS, Spark? etc.

For final presentations:

Start writing the final presentation right from the start and add elements little-by-little all day long. Articulate the reason you want to do the project, and the solution. Make it understandable to everyone.
If you wish, your work will be published on this website with your bio, name, etc.

Other details:

50 participants max
Food/drink: Only water, coffee and tea are provided. Attendees can order their own food to the venue, take a break to find a restaurant nearby or bring their own lunch.
Price: HK$50. We charge a fee to cover organisation costs. We are a not-for-profit organisation and will aim to keep the costs of our events as low as possible to make it accessible to all.

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.

 

Overwatch strategies revealed with data science

Ram de Guzman presented this analysis of Overwatch team strategies using scraped data from Winston’s Lab (which gathers it directly from game videos). His insight revealed how the best teams in South Korea arranged their teams and fought.

In the video he describes the process of gathering his data, then shows in impressive visualisations how that data relates to actual game strategy.

Watch his talk at our 6th unhackathon in March here:

 

And you can follow his project here.

Data science news round up

Our tight-knit community of data scientist have shared a wealth of news and inspiring projects from around the web over the past couple of months. Here is a brief round up of the more interesting articles, and remember, you can join in on our slack group.

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Millions of Chinese farmers reap benefits of huge crop experiment

An article that demonstrates the world changing potential of evidence based approaches to the world’s problems. For me, it’s also a reminder that it’s often not the latest buzzword or most glamourous topics that have the most impact.

Winning with Data Science

Next is an article examining the business and organisational side of data science. This is a topic that probably doesn’t get enough attention compared to the latest and coolest algorithm. It’s important for data scientists to take an interest in how organisations should adapt, if they don’t it will probably be decided by someone not qualified to make the decision!

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What Comes After Deep Learning?

This article examines whether deep learning is actually a blind alley and considers what new approaches might be next for data science. Also a brief examination of the question of US vs China in the AI “arms race”.

‘Who’s Leading AI’ Isn’t the Intelligent Question

Our final article explores the much talked about question of whether the US or China is winning and why it’s not the right question to ask.

If you found any of these articles interesting then do come and join the discussion on our Slack group, where you will also find details of meetups. https://datasciencehk.slack.com/

Women in data science – WiDS 2018

The Stanford Women in Data Science conference 2018  is starting on March 6th at 1am Hong-Kong time

Live Broadcast

We encourage everyone to follow the broadcast here 

You can tweet using the hashtag #WiDS2018Q

Program

The program can be found here, we reproduce it here for convenience in HK time zone

1:00-1:10am: Opening Remarks: Margot Gerritsen, Senior Associate Dean and Director of ICME, Stanford University
1:10-1:30am: Welcome Address: Maria Klawe, President, Harvey Mudd College
1:30-2:05am: Keynote Address: Leda Braga, CEO, Systematica Investments
2:05-2:10am Regional Event Check-in
2:10-2:50am: Technical Vision Talks:
     2:10-2:30am Mala Anand, EVP, President, SAP Leonardo Data Analytics
     2:30-2:50am Lada Adamic, Research Scientist Manager, Facebook
2:50-3:10am: Morning break
3:10-3:15am: WiDS Datathon Winners Announced
3:15-3:55am: Technical Vision Talks:
     3:15-3:35am: Nathalie Henry Riche, Researcher, Microsoft Research
     3:35-3:55am: Daniela Witten, Associate Professor of Statistics and Biostatistics, University of Washington
3:55am-4:30am: Keynote Address: Latanya Sweeney, Professor of Government and Technology in Residence, Harvard University
4:30-6:00am:  Lunch and Breakouts (NO LIVESTREAM)
6:00-6:35am: Keynote Address: Jia Li, Head of Cloud R&D, Cloud AI, Google
6:35-7:15am Technical Vision Talks:
     6:35-6:55am: Bhavani Thuraisingham,
Professor of Computer Science and Executive
Director of Cyber Research and Education Institute, University of Texas at Dallas
     6:55-7:15am: Elena Grewal, Head of Data Science, Airbnb
7:15-7:30am  Afternoon break 

7:30-7:35am Regional event check-in
7:35-8:15am Career Panel moderated by Margot Gerritsen
Bhavani Thuraisingham 
 Professor of Computer Science and Executive
Director of Cyber Research and Education Institute, University of Texas at Dallas
     Ziya Ma,  Vice President of Software and Services Group and Director of Big Data Technologies, Intel Corporation
     Elena Grewal Head of Data Science, Airbnb
     Jennifer Prendki, Head of Data Science, Atlassian
8:15-8:55am: Technical Vision Talks
     8:15-8:35am: Risa Wechsler, Associate Professor of Physics, Stanford University
     8:35-8:55am: Dawn Woodard, Senior Data Science Manager of Maps, Uber
8:55-9:00am: Closing Remarks