Kaggle: NOAA Fisheries Steller Sea Lion Population Count

27 марта 2017 — 27 июня 2017
Осталось 2 дня, 20 часов
Steller sea lions in the Aleutian Islands have declined 94 percent in the last 30 years. The endangered western population, found in the North Pacific, are the focus of conservation efforts which require annual population counts. Specially trained scientists at NOAA Fisheries Alaska Fisheries Science Center conduct these surveys using airplanes and unoccupied aircraft systems to collect aerial images. Having accurate population estimates enables us to better understand factors that may be contributing to lack of recovery of Stellers in this area.

DrivenData: Random Walk of the Penguins

29 апреля 2017 — 27 июня 2017
Осталось 2 дня, 20 часов
Data on penguin populations are limited because most monitored colonies are near permanent research stations and other sites are surveyed only sporadically. Because the data are so patchy, and time series relatively short, it has been difficult to build statistical models that can explain past dynamics or provide reliable future predictions. Your goal is to create better models to estimate populations for hard-to-reach sites in the Antarctic, and thereby greatly improve our ability to use penguins to monitor the health of the Southern Ocean!

Kaggle: Sberbank Russian Housing Market

28 апреля 2017 — 29 июня 2017
Осталось 4 дня, 20 часов
In this competition, Sberbank is challenging Kagglers to develop algorithms which use a broad spectrum of features to predict realty prices. Competitors will rely on a rich dataset that includes housing data and macroeconomic patterns. An accurate forecasting model will allow Sberbank to provide more certainty to their customers in an uncertain economy.

ILSVRC2017: ImageNet Large Scale Visual Recognition Challenge 2017

2 апреля 2017 — 30 июня 2017
Осталось 5 дней, 20 часов
This challenge evaluates algorithms for object localization/detection from images/videos at scale. 1. Object localization for 1000 categories. 2. Object detection for 200 fully labeled categories. 3. Object detection from video for 30 fully labeled categories.

Traffic Sign Detection under Challenging Conditions

31 мая 2017 — 1 июля 2017
Осталось 6 дней, 20 часов
We would like to encourage the competing teams to take behind-the-scenes pictures while working on the competition. You will be the first teams to work on VIP Cup so let’s make it special and show others later on how the competition process is thanks to your pictures. We will ask for these pictures as part of your submission package. We are confident that you will do a good job in the algorithmic side so you can also start thinking about demonstration ideas. The best three teams will give a presentation at ICIP 2017, which should include a demonstration/video showcase. Presentation session will be the time for you to shine and get all the recognition you deserve.

CIKM AnalytiCup 2017: Lazada Product Title Quality Challenge

1 мая 2017 — 1 июля 2017
Осталось 6 дней, 20 часов
On Lazada, we have millions of products across thousands of categories. To stand out from the crowd, sellers employ creative, sometimes disruptive efforts to improve their search relevancy or attract the attention of customers. Product titles like "hot sexy red clutch rug sack travel backpack unisex cheap with free gift" degenerate user experience by cluttering the site with irrelevant, misleading titles.

DeepHack Qualification: Human or Machine Generated Text?

13 июня 2017 — 7 июля 2017
Осталось 1 неделя, 5 дней
А 24/7 week-long sci-hack summer school with the goal to develop best algorithms that can evaluate dialogue response quality automatically.

Kaggle: iNaturalist Challenge at FGVC 2017

2 июня 2017 — 7 июля 2017
Осталось 1 неделя, 5 дней
As part of the FGVC4 workshop at CVPR 2017 we are conducting the iNat Challenge 2017 large scale species classification competition, sponsored by Google. It is estimated that the natural world contains several million species of plants and animals. Without expert knowledge, many of these species are extremely difficult to accurately classify due to their visual similarity. The goal of this competition is to push the state of the art in automatic image classification for real world data that features fine-grained categories, big class imbalances, and large numbers of classes.

Kaggle: iMaterialist Challenge at FGVC 2017

2 июня 2017 — 7 июля 2017
Осталось 1 неделя, 5 дней
In this competition, FGVC workshop organizers and Google challenge you to develop algorithms that will help with the an important step towards automatic product detection–accurately assigning attribute labels for product images. Individuals/Teams with top submissions will be invited to present their work live at the FGVC4 workshop.

Kaggle: Mercedes-Benz Greener Manufacturing

30 мая 2017 — 10 июля 2017
Осталось 2 недели, 1 день
In this competition, Daimler is challenging Kagglers to tackle the curse of dimensionality and reduce the time that cars spend on the test bench. Competitors will work with a dataset representing different permutations of Mercedes-Benz car features to predict the time it takes to pass testing. Winning algorithms will contribute to speedier testing, resulting in lower carbon dioxide emissions without reducing Daimler’s standards.

Datascience.net: Prévision de la consommation électrique

11 мая 2017 — 16 июля 2017
Осталось 3 недели
RTE réalise quotidiennement des prévisions de consommation d’électricité qui permettent d’assurer à tout instant l’équilibre entre l’offre et la demande d’électricité et, ainsi, de garantir la sûreté du système électrique. L'objectif de ce challenge est d'effectuer une prévision déterministe à court terme de la consommation nationale et régionale d’électricité en France.

MLBootCamp V: Предсказание ССЗ

16 июня 2017 — 16 июля 2017
Осталось 3 недели
В рамках конкурса вам нужно предсказать наличие сердечно-сосудистых заболеваний по результатам классического врачебного осмотра. Датасет сформирован из 100.000 реальных клинических анализов.

Kaggle: Planet Understanding the Amazon from Space

20 апреля 2017 — 20 июля 2017
Осталось 3 недели, 4 дня
In this competition, Planet and its Brazilian partner SCCON are challenging Kagglers to label satellite image chips with atmospheric conditions and various classes of land cover/land use. Resulting algorithms will help the global community better understand where, how, and why deforestation happens all over the world - and ultimately how to respond.

ECML PKDD 2017: Multi-Plant Photovoltaic Energy Forecasting Challenge

1 июля 2017 — 24 июля 2017
Осталось 4 недели, 1 день
The urgent need to reduce pollution emission has made renewable energy a strategic European Union (EU) and international sector. This has resulted in an increasing presence of renewable energy sources and thus, significant distributed power generation. The main challenges faced by this new energy market are grid integration, load balancing and energy trading. In order to face these challenges, it is of paramount importance to monitor the production and consumption of energy, both at the local and global level, to store historical data and to design new, reliable prediction tools. In this challenge, we focus our attention on photovoltaic (PV) power plants, due to their wide distribution in Europe. During the last years, the forecast of PV energy production has received significant attention since photovoltaics are becoming a major source of renewable energy for the world. Forecast may apply to a single renewable power generation system, or refer to an aggregation of large numbers of systems spread over an extended geographic area.

ECML PKDD 2017: Mars Express Power Challenge

8 июня 2017 — 24 июля 2017
Осталось 4 недели, 1 день
The goal of this challenge is to analyze the provided training set of Mars Express data, including context data (explanatory/predictor variables) and measurements of the electric current (target variables) in each thermal subsystem node, to predict the average electric current of 33 thermal power lines per hour of the test set containing only the context data.

ECML PKDD 2017: Time Series Land Cover Classification Challenge

1 июля 2017 — 24 июля 2017
Осталось 4 недели, 1 день
Nowadays, modern earth observation programs produce huge volumes of satellite images time series (SITS) that can be useful to monitor geographical areas through time. How to efficiently analyze such kind of information is still an open question in the remote sensing field. In the context of land cover classification, exploiting time series of satellite images, instead that one single image, can be fruitful to distinguish among classes based on the fact they have different temporal profiles. The objective of this challenge is to bring closer the Machine Learning and Remote Sensing communities to work on such kind of data. The Machine Learning community has the opportunity to validate and test their approaches on real world data in an application context that is getting more and more attention due to the increasing availability of SITS data while, this challenge offers to the Remote Sensing experts a way to discover and evaluate new data mining and machine learning methods to deal with SITS data. The challenge involves a multi-class single label classification problem where the examples to classify are pixels described by the time series of satellite images and the prediction is related to the land cover of associated to each pixel. A more detailed description follows.

General AI Challenge: Gradual Learning - Learning Like a Human

15 февраля 2017 — 14 августа 2017
Осталось 1 месяц, 2 недели
You will be programming and training an AI agent that will engage in a dialogue with the CommAI-Env environment. They will exchange bytes of information, and in addition the environment will give feedback signals to the agent to guide its behavior.

Kaggle: Instacart Market Basket Analysis

17 мая 2017 — 14 августа 2017
Осталось 1 месяц, 2 недели
Whether you shop from meticulously planned grocery lists or let whimsy guide your grazing, our unique food rituals define who we are. Instacart, a grocery ordering and delivery app, aims to make it easy to fill your refrigerator and pantry with your personal favorites and staples when you need them. After selecting products through the Instacart app, personal shoppers review your order and do the in-store shopping and delivery for you.

The PhysioNet/Computing in Cardiology Challenge 2017

1 февраля 2017 — 1 сентября 2017
Осталось 2 месяца, 1 неделя
The 2017 PhysioNet/CinC Challenge aims to encourage the development of algorithms to classify, from a single short ECG lead recording (between 30 s and 60 s in length), whether the recording shows normal sinus rhythm, atrial fibrillation (AF), an alternative rhythm, or is too noisy to be classified.

Kaggle: Passenger Screening Algorithm Challenge

22 июня 2017 — 16 декабря 2017
Осталось 5 месяцев, 3 недели
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.