San Francisco, California
London, United Kingdom
NTT Innovation Institute Machine Learning Hackathon
When: 6 p.m. June 20-7 p.m. June 21
What: Create innovative use cases for machine learning and build a proof-of-concept by the end of the event.
Who: Data scientists; Big Data entrepreneurs; and domain experts in other areas that may need machine learning, including security, wearables, e-commerce, mobile apps and more.
Where: NestGSV, 425 Broadway St., Redwood City, CA, 94063
6 p.m.: Kickoff dinner and social networking.
7 p.m.: Opening remarks.
7:30 p.m. Idea pitches and team formation.
8 p.m. Deadline to submit ideas to the system. Each team will receive access to cloud resources.
8:30 p.m.: Coding begins.
10 a.m.: Breakfast
5 p.m.: Projects due.
5:30 p.m.: Dinner
6 p.m.: Five to 10-minute pitch from each team.
6:30 p.m.: Judging
7 p.m.: Winners announced and closing ceremony.
1. Teams can have one to five members, consisting of any combination of idea person, data scientist, software engineer and others.
2. Any data source can be used.
3. All teams retain full ownership of the code developed during the hackathon.
Develop machine learning scenarios, code and data visualization. We have loaded a few public data sets, but you can use your own data sets or any other public data sets. Explain in your concluding presentation the reasons for choosing a specific machine learning tool set and framework for the selected scenario.
You can use any machine learning library you like, but we encourage you to try out Jubatus, an open-source machine learning framework developed by NTT. You can find all necessary resources below to get you started.
Jubatus Official Website:
Jubatus QuickStart VM:
(ID: jubatus, Password: acinonyx)
Tutorial Slides about Jubatus:
Computer failure data repository. Detailed failure data from a variety of large production systems https://www.usenix.org/cfdr
Data generated from TCP dump that can be used to train a network intrusion detection system http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html
Rating data sets from the MovieLens web site http://grouplens.org/datasets/movielens/
Google+ social network http://snap.stanford.edu/data/egonets-Gplus.html
Stanford web graph http://snap.stanford.edu/data/web-Stanford.html
Airline on-time performance record http://stat-computing.org/dataexpo/2009/
First place: $1,000 cash and $1,000 Dimension Data cloud credit.
Second place: $500 cash and $500 Dimension Data cloud credit.
Third place: $300 Dimension Data cloud credit.
Audience favorite: $500 cash and $500 Dimension Data cloud credit.
Visualization (meaningful representation of the data and results).
Presentation (details of the use case, description of the tool set and the reasons for choosing it and business applicability).
Use of real-time machine learning (for example, Jubatus) earns extra points.
If you have any questions, please send an email with the subject line NTT Hackathon to firstname.lastname@example.org.
When & Where
NestGSV accelerates global innovation by launching Innovation Labs around important trends in the growth economy, such as Big Data, Ed Tech, Sustainability and Mobility.
We offer a 72,000 square foot campus at the epicenter of Silicon Valley, along with diverse programs to help innovators thrive. We specialize in startup relationships, corporate partnerships, education, accelerator programs, hackathons, ideathons, and industry networking.
For partnership inquiries, email us at info@nestGSV.com.