Un-hackathon #10

Our 10th Hackathon for Data Science: 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 other people’s. And in the beginning of the day we will host some fantastic industry specialists to share their experiences operating in the data science field.

Signup at: Eventbrite, Meetup, Facebook

The event will be held at the South China Morning Post offices at Times Square

 

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.
50HKD 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: 50 HKD. We charge a fee to cover venue and food 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 #8

Our 8th Hackathon for Data Science: 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 other people’s. And in the beginning of the day we will host some fantastic industry specialists to share their experiences operating in the data science field.

Signup at: Eventbrite, Meetup, Facebook

naked-hub

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:
16F, 40-44 Bonham Strand, Sheung Wan, Hong Kong

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
50HKD 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: 50 HKD. We charge a fee to cover venue and food 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.

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

 

Unhackathon #5: Discovering trends in property data and scams in ICOs

Our fifth un-hackathon kicked off the year with 30 eager data scientists attending. The event at Makerhive in Kennedy town was the first of the year and combined industry talks with project based collaboration.

As the mercury dipped outside the fires of creativity burned bright among our attendees. Five project leaders suggested projects to focus the skills of our data scientists on uncovering new insights into the property market in Hong Kong, with a 1.6 million row record of transactions over the past 20 years. Another project aimed to discover whether public data can spot a scam initial coin offering, or ICO.

Presentations

IMG_20180204_103740_HDR

Pranav Agrawal, an HK University of Science and Technolology student, presented a code tutorial on Multi-layer perceptrons in PyTorch. The in-depth, code-centric tutorial took us step by step through the process. We can share links to the documentation here:

Github

Presentation


Hang Xu presented his method of looking at DNA using the word-to-vector model. He said his method of adapting the word2vec model to analyse DNA was superior to the best usage of the current method of analysing DNA using a one-hot vector method.

Presentation

Projects

  • Guy’s property data analysis
  • Jenson’s ICO scam detector
  • Kirill’s Ansible machine learning speed booster

Property data analysis

Using a 1.2gb table of 1.6 million property transactions in Hong Kong, from 1997 to today, this group looked for trends and insights in the property market. Some of the central questions were quantifying the rate that property prices were growing in relation to wage growth in the city.

They found some bargains, even in the current market. See their presentation with their findings.

Ansible speed boosting for NumPy and R

A lot of machine learning tools depend on matrix manipulation libraries, e.g. NumPy. In a basic configuration it uses CPU for linear algebra computations, such as matrix multiplication, SVD or Eigenvalues decomposition. OpenBLAS speeds computations 4-10x via Fortran binding.

Github

See their presentation here.

Is this ICO a scam?

The group pulled a list of over 1600 ICOs from the past two years, and with the question of whether they could establish whether it is a scam, evaluated their value. The second step was to gather the return on investment for each of the ICOs, and the countries they were reported to have come from.

See their presentation and findings here.

Job explorer

Morris Wong worked on scraping a dataset to build a structured system to help jobseekers vet a company before joining. Using stealjobs.com data he aims to build an explorer in the shape of GitXplore using four metrics: income, working hours, promotion prospect, happiness. The data is user generated.

See you all at our next event in March.