DataHack Challenges - The hackathon challenges offered by top data companies
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DataChallenges

This is a list of sponsor challenges at DataHack events.

You can find us on our website, Facebook, Meetup, YouTube and Twitter, and also join our monthly newsletter.



DataHack 2016

Intel - Data Science for Social Good

Description: Are you passionate about making the world a better place? Are you excited to use AI for the benefit of mankind? Intel, DataHack 2016's co-host, is posing the AI for Social Good Challenge. Intel will award a cool prize to each member of the team whose project most effectively utilizes AI to address a social issue.

Potential Datasets: https://github.com/shreyashankar/datasets-for-good

Final - The Taxi Challenge

Description: A taxi goes from Chinatown to Times Square. How long will it take to arrive? In this challenge, you are given data on taxi rides in New York, containing information on each ride such as the start and end points, date, time of day, distance, etc. The data is available here. Our purpose is to predict the travel time (in logarithmic scale) of a ride. The data is split to train and test sets, and we can use both general data of the ride with local data on similar rides from the train set.

Repository: https://github.com/RocketDataScientist/DataHack-2017

Wix - User Action Prediction

Description: WIX collects logs of user actions within its platform. One of the main tasks of our Data Science team is understanding and predicting user behavior in order to optimize user experience and company revenue. Our team focuses on building models that are compact & efficient without compromising on accuracy. Using historical user event data we want to predict if a user performs a specific action ("the target action") within 14 days from the last available activity data.

Windward - You remind me of a ship I know...

Description: Windward is a data and analytics company making sense of ship and cargo movements around the world. Our Data Platform takes raw, unstandardized big data from multiple sources – which is often partial and unreliable - and uses ML to fuse the data and analyze each ship's actual behavior to determine ship identities and what they are doing. This helps to create actionable, insightful knowledge about what’s happening at sea from otherwise hard-to-interpret, noisy data.

One of the most important data features is ship type. A ship type describes what class of ship it is and could be anything from a small fishing vessel to a massive oil tanker. Most ships report their true type but some don’t, which means their designation labels are either incorrect or missing. In this case, we have to infer it ourselves.

In our data challenge you will help us predict ship type according to ship behavior. We will provide information about ship activities (meetings with other vessels, port visits, etc.). Some ships will be labeled with their type and other labels will be missing. The challenge is to infer the type of unlabeled ships based on labeled ships exhibiting similar behavior. The underlying assumption is that ships engaged in similar activities (e.g. frequenting the same ports, meeting with the same ships) are more likely to be of the same type.

This is, in a way, the ship version of “people similar to you” used on social websites. So, are you up to the challenge?


DataHack 2017

Intel - Data Science for Social Good

Description: Are you passionate about making the world a better place? Are you excited to use AI for the benefit of mankind? Intel, DataHack 2017's co-host, is posing the AI for Social Good Challenge. Intel will award a cool prize to each member of the team whose project most effectively utilizes AI to address a social issue.

Potential Datasets: https://github.com/shreyashankar/datasets-for-good

Rafael - It Takes a Rocket (data) Scientist!

Description: Ever wondered how it feels to press the red button and take down missiles? Well this challenge will get you fairly close to that goal! You will be provided with short length trajectories (5-15s) and you’ll need to decide what type of threat you are facing. This challenge, provided by Rafael, combines both supervised and unsupervised learning.

Repository: https://github.com/RocketDataScientist/DataHack-2017

OrCam - Instagram Challenge

Description: You think finding a needle in a haystack is easy-peasy-lemon-squeezy? Well you’re in for a treat! In the instagram challenge you will receive ~1M photos taken from 10K albums, your task will be to find the images that belong to the album’s owner. But not to worry, OrCam is here to help (a bit) - for each image you will be given some metadata and a descriptor for the face residing in it.

SparkBeyond - Word Disambiguation

Description: Did you always dream about being a detective? In that case we’ve got a great mystery for you to solve! In the word disambiguation challenge you will receive a sentence and a single token, you will then need to utilize all of your detective skills to find the right Wikipedia page defining this token.


DataHack 2018

Intel - Data Science for Social Good

Description: Are you passionate about making the world a better place? Are you excited to use AI for the benefit of mankind? Intel, DataHack 2018's co-host, is posing the AI for Social Good Challenge. Intel will award a cool prize to each member of the team whose project most effectively utilizes AI to address a social issue.

Presentation: https://github.com/DataHackIL/DataChallenges/blob/master/2018/Intel_challenge_datahack_2018.pdf

Potential Datasets: https://github.com/shreyashankar/datasets-for-good

Innoviz Technologies - Rigid Motion Segmentation

Description: Are you passionate about making widespread, impactful global changes? Autonomous vehicles represent one of the biggest revolutions mankind has ever seen and they will affect every aspect of our daily lives. In this challenge you will help to enable the autonomous car revolution. Teams undertaking Innoviz’s Rigid Motion Segmentation Challenge will solve the problem of decomposing LIDAR data (point cloud) into background and moving objects.

Presentation: https://github.com/DataHackIL/DataChallenges/blob/master/2018/innoviz_challenge_datahack_2018.pdf

Repository: https://github.com/InnovizTech/DataHack2018

Lightricks - Churn Prediction

Description: Want to help a top Jerusalem startup pilot churn prediction on an actual project for its flagship app - a product already used by millions all over the world? Sift through noisy data to discover patterns predicting who will churn and even when these ‘suspects’ are likely to unsubscribe, to earn yourself a lucrative reward at DataHack 2018!

Presentation: https://github.com/DataHackIL/DataChallenges/blob/master/2018/Lightricks_challenge_2018.pdf

Repository: https://github.com/Lightricks/datahack

Microsoft - The Math Teacher Challenge

Description: Microsoft Open Source team is proud to host the first “The Math Teacher” challenge in Israel, where you can leverage your NLP skills and the Azure Open Cloud to understand and solve complex math problems. Microsoft's "The Math Teacher” Challenge is a NLP Challenge for building a personal math teacher using natural language for understanding and reasoning capacities around Math. The goal is to build and NLP model that can perform automatic problem solving (especially math word problems) written in natural language. Your mission, if you choose to accept it, is to build a model that can return the highest amount of correct answers above a given baseline on the number_word_std test set.

Presentation: https://github.com/DataHackIL/DataChallenges/blob/master/2018/Microsoft_challenge_datahack_2018.pdf

Repository: https://github.com/aribornstein/MathTeacherChallenge/