Hansen House - Center for Design, Media and Technology. Gdalyahu Alon 14, Jerusalem.
DataHack is all about data. Every project is required to have processing and/or analysis of some interesting data at its core. It can be a machine learning algorithm, a statistical analysis or producing deep insights automatically with data mining techniques.
The event will take place between Wednesday, 15:30, September 21st and Friday, 13:30, September 23rd, 2016.
Registration to the event is open to all - students, researches, designers and industry professionals. Teams of up to 5 people may register.
We will provide you with different data sets from our sponsors, partners and online sources, but you are free to bring your own data. Have a data-related question?
Contact our data team at firstname.lastname@example.org
Besides a yearly hackathon, DataHack is also a vibrant community of data scientists and machine learning experts in which you can take part through our Facebook page, the DataTalks meetup series and our newsletter!
Intel Israel will be giving an ASUS ZenPad 10 tablet to each member of the team whose project most effectively utilizes machine learning or data science to address a social issue!
- Final -
Bose QuietComfort 35 headphones (for each team member)
- Wix -
Amazon Echo (for each team member)
- Windward -
The person in charge of the best solo project of DataHack 2016 will win one of Varidesk's adjustable standing desks!
Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem
Benin School of Engineering and Computer Science & The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem
Senior Data Scientist,
Intel Advanced Analytics
Editor in Chief & COO,
Department of Statistics,
The Hebrew University of Jerusalem
Some of our sponsors will provide you with specific prize challenges. Check them out!
Teams participating in DataHack are free to use any data set open for public use or for which they have free access. However, we also want to offer you a curated list of data sets for you to consider.
A taxi goes from Chinatown to Times Square. How long will it take to arrive?
Try and predict user behavior on the Wix platfrom from user action history.
Love the oceans? Try and make sense of data on ship movement worldwide.