DrivenData: Pri-matrix Factorization

21 октября 2017 — 15 декабря 2017
Осталось 2 дня, 15 часов
In this project, data tagging by a global community through the Chimp&See Zooniverse project feeds into algorithm development by a global community now reading this description. You'll find here one of the largest labeled camera trap datasets for you to test your skills and help researchers unlock the secrets of life on Earth!

Topcoder: IAPRA The functional Map of the World Challenge

1 августа 2017 — 15 декабря 2017
Осталось 2 дня, 15 часов
The functional Map of the World (fMoW) Challenge invites solvers from around the world to develop deep learning and other automated techniques to classify points of interest from satellite imagery. The goal of the challenge is to facilitate breakthroughs in object identification and classification to automatically identify facility, building, and land use.

Kaggle: Cdiscount’s Image Classification Challenge

14 сентября 2017 — 15 декабря 2017
Осталось 2 дня, 15 часов
In this challenge you will be building a model that automatically classifies the products based on their images. As a quick tour of Cdiscount.com's website can confirm, one product can have one or several images. The data set Cdiscount.com is making available is unique and characterized by superlative numbers in several ways: - Almost 9 million products: half of the current catalogue - More than 15 million images at 180x180 resolution - More than 5000 categories: yes this is quite an extreme multi-class classification!

Kaggle: Passenger Screening Algorithm Challenge

22 июня 2017 — 16 декабря 2017
Осталось 3 дня, 15 часов
Currently, TSA purchases updated algorithms exclusively from the manufacturers of the scanning equipment used. These algorithms are proprietary, expensive, and often released in long cycles. In this competition, TSA is stepping outside their established procurement process and is challenging the broader data science community to help improve the accuracy of their threat prediction algorithms. Using a dataset of images collected on the latest generation of scanners, participants are challenged to identify the presence of simulated threats under a variety of object types, clothing types, and body types. Even a modest decrease in false alarms will help TSA significantly improve the passenger experience while maintaining high levels of security.

Boosters: Ticketland ML Contest

23 октября 2017 — 17 декабря 2017
Осталось 4 дня, 15 часов
Участникам чемпионата предстоит предсказать вероятность клика на шоу, которое появилось в поисковой выдачи сайта Ticketland.ru. В качестве датасета участникам предоставляются различные данные о шоу и известные данные о юзерах сайта.

Kaggle: WSDM - KKBox's Music Recommendation Challeng

28 сентября 2017 — 18 декабря 2017
Осталось 5 дней, 15 часов
WSDM has challenged the Kaggle ML community to help solve these problems and build a better music recommendation system. The dataset is from KKBOX, Asia’s leading music streaming service, holding the world’s most comprehensive Asia-Pop music library with over 30 million tracks. They currently use a collaborative filtering based algorithm with matrix factorization and word embedding in their recommendation system but believe new techniques could lead to better results.

Kaggle: WSDM - KKBox's Churn Prediction Challenge

19 сентября 2017 — 18 декабря 2017
Осталось 5 дней, 15 часов
In this competition you’re tasked to build an algorithm that predicts whether a user will churn after their subscription expires. Currently, the company uses survival analysis techniques to determine the residual membership life time for each subscriber. By adopting different methods, KKBOX anticipates they’ll discover new insights to why users leave so they can be proactive in keeping users dancing. Winners will present their findings at the WSDM conference February 6-8, 2018 in Los Angeles, CA. For more information on the conference, click here.

DrivenData: DengAI Predicting Disease Spread

1 января 2017 — 22 декабря 2017
Осталось 1 неделя, 2 дня
Accurate dengue predictions would help public health workers ... and people around the world take steps to reduce the impact of these epidemics. But predicting dengue is a hefty task that calls for the consolidation of different data sets on disease incidence, weather, and the environment.

Tinkoff Fintech: соревнование по спутниковым снимкам

22 ноября 2017 — 24 декабря 2017
Осталось 1 неделя, 4 дня
Мы решили попробовать новые источники информации: спутниковые снимки высокого разрешения. Предлагаем две задачи на их анализ: про здания и автомобили и про здания и тени.

crowdAI: AI-generated music challenge

1 декабря 2017 — 31 декабря 2017
Осталось 2 недели, 4 дня
In this challenge, participants are tasked to generate an AI model that learns on a large data set of music (in the form of MIDI files), and is then capable of producing its own music. Concretely, the model must produce a music piece in response to a short “seed” MIDI file that is given as input.

RUSSE 2018 Word Sense Induction and Disambiguation Shared Task

1 ноября 2017 — 15 января 2018
Осталось 1 месяц
We invite you to participate in the shared task on Word Sense Induction and Disambiguation for the Russian Language co-located with the Dialogue 2018 conference. TLDR: You are given a word, e.g. "замок" and a bunch of text fragments (aka “contexts”) where this word occurrs, e.g. "замок владимира мономаха в любече" and "передвижению засова ключом в замке". You need to cluster these contexts in the (unknown in advance) number of clusters which correspond to various senses of the word. In this example you want to have two groups with the contexts of the “lock” and the “castle” senses of the word "замок".

Kaggle: Corporación Favorita Grocery Sales Forecasting

19 октября 2017 — 16 января 2018
Осталось 1 месяц
Corporación Favorita has challenged the Kaggle community to build a model that more accurately forecasts product sales. They currently rely on subjective forecasting methods with very little data to back them up and very little automation to execute plans. They’re excited to see how machine learning could better ensure they please customers by having just enough of the right products at the right time.

Kaggle: Zillow’s Home Value Prediction (Zestimate)

24 мая 2017 — 17 января 2018
Осталось 1 месяц
Zillow’s Zestimate home valuation has shaken up the U.S. real estate industry since first released 11 years ago. A home is often the largest and most expensive purchase a person makes in his or her lifetime. Ensuring homeowners have a trusted way to monitor this asset is incredibly important. The Zestimate was created to give consumers as much information as possible about homes and the housing market, marking the first time consumers had access to this type of home value information at no cost.

Kaggle: TensorFlow Speech Recognition Challenge

15 ноября 2017 — 17 января 2018
Осталось 1 месяц
In this competition, you're challenged to use the Speech Commands Dataset to build an algorithm that understands simple spoken commands. By improving the recognition accuracy of open-sourced voice interface tools, we can improve product effectiveness and their accessibility.

Kaggle: Statoil/C-CORE Iceberg Classifier Challenge

24 октября 2017 — 24 января 2018
Осталось 1 месяц, 1 неделя
In this competition, you’re challenged to build an algorithm that automatically identifies if a remotely sensed target is a ship or iceberg. Improvements made will help drive the costs down for maintaining safe working conditions.

DrivenData: Concept to Clinic

4 августа 2017 — 25 января 2018
Осталось 1 месяц, 1 неделя
There is a daunting chasm between research algorithms and clinical practice. We want to bridge this gap by developing an end-to-end application, as a community, that connects the predictive power of machine learning with functional software tested against errors and a clean user interface focused on clinical use.

NLP Challenges for Detecting Medication and Adverse Drug Events from Electronic Health Records

1 ноября 2017 — 1 февраля 2018
Осталось 1 месяц, 2 недели
Adverse drug events (ADEs) are common and occur in approximately 2-5% of hospitalized adult patients. Each ADE is estimated to increase healthcare cost by more than $3,200. Severe ADEs rank among the top 5 or 6 leading causes of death in the United States. Prevention, early detection and mitigation of ADEs could save both lives and dollars. Employing natural language processing (NLP) techniques on electronic health records (EHRs) provides an effective way of real-time pharmacovigilance and drug safety surveillance. We’ve annotated 1092 EHR notes with medications, as well as relations to their corresponding attributes, indications and adverse events. It provides valuable resources to develop NLP systems to automatically detect those clinically important entities. Therefore we are happy to announce a public NLP challenge, MADE1.0, aiming to promote deep innovations in related research tasks, and bring researchers and professionals together exchanging research ideas and sharing expertise. The ultimate goal is to further advance ADE detection techniques to improve patient safety and health care quality.

Kaggle: Recruit Restaurant Visitor Forecasting

28 ноября 2017 — 7 февраля 2018
Осталось 1 месяц, 3 недели
In this competition, you're challenged to use reservation and visitation data to predict the total number of visitors to a restaurant for future dates. This information will help restaurants be much more efficient and allow them to focus on creating an enjoyable dining experience for their customers.

Kaggle: Plant Seedlings Classification

22 ноября 2017 — 13 февраля 2018
Осталось 2 месяца
Can you differentiate a weed from a crop seedling?

Kaggle: Mercari Price Suggestion Challenge

21 ноября 2017 — 22 февраля 2018
Осталось 2 месяца, 1 неделя
In this competition, Mercari’s challenging you to build an algorithm that automatically suggests the right product prices. You’ll be provided user-inputted text descriptions of their products, including details like product category name, brand name, and item condition.