Kaggle: Google Landmark Retrieval Challenge

3 февраля 2018 — 22 мая 2018
Осталось 1 день, 19 часов
In this competition, Kagglers are given query images and, for each query, are expected to retrieve all database images containing the same landmarks (if any).

Kaggle: Google Landmark Recognition Challenge

3 февраля 2018 — 22 мая 2018
Осталось 1 день, 19 часов
Many Kagglers are familiar with image classification challenges like the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), which aims to recognize 1K general object categories. Landmark recognition is a little different from that: it contains a much larger number of classes (there are a total of 15K classes in this challenge), and the number of training examples per class may not be very large. Landmark recognition is challenging in its own way.

Boosters: Rosbank ML Competition

27 апреля 2018 — 28 мая 2018
Осталось 1 неделя
Задача 1. На обе задачи участникам даётся один датасет, который содержит историю транзакций клиентов за 3 месяца льготного использования банковского продукта, в первой задаче вам предстоит решить задачу бинарной классификации – спрогнозировать отток клиентов. Задача 2. Во второй задаче вам нужно предсказать объём транзакций через POS терминал за следующие три месяца использования продукта.

Boosters: Бабушкин суп из данных планирование рекламы

17 апреля 2018 — 30 мая 2018
Осталось 1 неделя, 2 дня
Для того, чтобы спланировать реламную кампанию, рекламодателю необходимо знать величину Revenue per Click — сколько он заработает с каждого клика на объявление в определенном контексте (устройство, географическая локация пользователя, группа объявлений). Эту величину и предлагается предсказать. Более подробное описание задачи — на странице с данными.

Kaggle: iMaterialist Challenge (Furniture) at FGVC5

5 марта 2018 — 30 мая 2018
Осталось 1 неделя, 2 дня
In this competition, FGVC5 workshop organizers and Malong Technologies challenge you to develop algorithms that will help with an important step towards automatic product recognition – to accurately assign category labels for furniture and home goods images. Individuals/Teams with top submissions will be invited to present their work live at the FGVC5 workshop.

Kaggle: iMaterialist Challenge (Fashion) at FGVC5

3 апреля 2018 — 30 мая 2018
Осталось 1 неделя, 2 дня
In this competition, FGVC workshop organizers with Wish and Malong Technologies challenge you to develop algorithms that will help with an important step towards automatic product detection – to accurately assign attribute labels for fashion images. Individuals/Teams with top submissions will be invited to present their work live at the FGVC5 workshop.

KDD CUP of Fresh Air 2018

13 апреля 2018 — 31 мая 2018
Осталось 1 неделя, 3 дня
Participants are requested to predict concentration levels of several pollutants, include PM2.5, over the coming 48 hours for two cities: Beijing, China, and London, UK. On each day throughout the competition, air quality data and meteorological data for both cities will be provided on the hourly basis. For example, on May 14, the participants will be able to access historical data up to May 14 (including), and will have to predict the pollution level for May 15 and 16. Over a period of 24 hours (by 23:59 UTC), each team will be allowed to make no more than 3 submissions to predict 48 hours of air quality results, starting from 0:00 UTC of the next day. You can more details on the submission API and the submission file format on the 'data' page or in this tutorial.

crowdAI: Mapping Challenge

1 апреля 2018 — 31 мая 2018
Осталось 1 неделя, 3 дня
In this challenge we want to explore how Machine Learning can help pave the way for automated analysis of satellite imagery to generate relevant and real-time maps.

OpenAI Retro Contest

5 апреля 2018 — 5 июня 2018
Осталось 2 недели, 1 день
We believe that the next step for reinforcement learning is to leverage past experience to quickly learn new environments. Current algorithms are very prone to memorization and can't adapt well to new situations. While this contest focuses on video game levels, we hope the winning techniques will be applicable to a wide variety of domains. The contest will run from April 5 to June 5 (2 months) and winners will receive some pretty cool trophies.

Kaggle: iNaturalist Challenge at FGVC5

22 февраля 2018 — 5 июня 2018
Осталось 2 недели, 1 день
As part of the FGVC5 workshop at CVPR 2018 we are conducting the iNat Challenge 2018 large scale species classification competition. 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 a large number of fine-grained categories with high class imbalance.

CVPR 2018: WebVision Challenge 2018

18 марта 2018 — 8 июня 2018
Осталось 2 недели, 4 дня
The recent success of deep learning has shown that a deep architecture in conjunction with abundant quantities of labeled training data is the most promising approach for most vision tasks. However, annotating a large-scale dataset for training such deep neural networks is costly and time-consuming, even with the availability of scalable crowdsourcing platforms like Amazon’s Mechanical Turk. As a result, there are relatively few public large-scale datasets (e.g., ImageNet and Places2) from which it is possible to learn generic visual representations from scratch.

Kaggle: CVPR 2018 WAD Video Segmentation Challenge

5 апреля 2018 — 12 июня 2018
Осталось 3 недели, 1 день
When you're driving, how important is it to be able to quickly tell the difference between a person vs. a stop sign? It's a hugely important, but typically very simple, distinction that you would make reflexively. Autonomous vehicles are not able to do this quite as effortlessly. This challenge, hosted by the 2018 CVPR workshop on autonomous driving (WAD), asks you to help give autonomously driven vehicles the same edge. Using an unprecedented dataset, you're asked to segment movable objects, such as cars and pedestrians, at instance level within image frames.

Kaggle: Avito Demand Prediction Challenge

25 апреля 2018 — 28 июня 2018
Осталось 1 месяц, 1 неделя
In their fourth Kaggle competition, Avito is challenging you to predict demand for an online advertisement based on its full description (title, description, images, etc.), its context (geographically where it was posted, similar ads already posted) and historical demand for similar ads in similar contexts. With this information, Avito can inform sellers on how to best optimize their listing and provide some indication of how much interest they should realistically expect to receive.

RecSys Challenge 2018: Spotify

1 апреля 2018 — 30 июня 2018
Осталось 1 месяц, 1 неделя
Spotify is an online music streaming service with over 140 million active users and over 30 million tracks. One of its popular features is the ability to create playlists, and the service currently hosts over 2 billion playlists. This year's challenge focuses on music recommendation, specifically the challenge of automatic playlist continuation. By suggesting appropriate songs to add to a playlist, a Recommender System can increase user engagement by making playlist creation easier, as well as extending listening beyond the end of existing playlists.

Tianchi: FashionAI Global Challenge 2018 Key Points Detection of Apparel

1 апреля 2018 — 5 июля 2018
Осталось 1 месяц, 2 недели
Upgrades in consumption patterns mean that there is significant room for potential growth in the fashion industry. According to official statistics from different countries, the market value of the global apparel market is worth over USD 3 trillion. Although artificial intelligence (AI) technology has been evolving along with the fashion industry, there are still different challenges in different areas that need to be addressed. The Vision & Beauty Team of the Alibaba Group and the Institute of Textile and Clothing of The Hong Kong Polytechnic University are pleased to announce that they are co-organizing the FashionAI Global Challenge 2018, which will jointly launch a revolutionary dataset which integrates both professional fashion knowledge and machine learning formulation. Concurrently the world's first FashionAI Global Challenge offers RMB 1.34 million prize pool, you are invited to solve the imminent issues on the application of AI in fashion.

Tianchi FashionAI Global Challenge 2018 Attributes Recognition of Apparel

1 апреля 2018 — 5 июля 2018
Осталось 1 месяц, 2 недели
Upgrades in consumption patterns mean that there is significant room for potential growth in the fashion industry. According to official statistics from different countries, the market value of the global apparel market is worth over USD 3 trillion. Although artificial intelligence (AI) technology has been evolving along with the fashion industry, there are still different challenges in different areas that need to be addressed. The Vision & Beauty Team of the Alibaba Group and the Institute of Textile and Clothing of The Hong Kong Polytechnic University are pleased to announce that they are co-organizing the FashionAI Global Challenge 2018, which will jointly launch a revolutionary dataset which integrates both professional fashion knowledge and machine learning formulation. Concurrently the world's first FashionAI Global Challenge offers RMB 1.34 million prize pool, you are invited to solve the imminent issues on the application of AI in fashion.

CodRep: Machine Learning on Source Code Competition

8 апреля 2018 — 14 июля 2018
Осталось 1 месяц, 3 недели
CodRep is a machine learning competition on source code data. The goal of the competition is provide different communities (machine learning, software engineering, programming language) with a common playground to test and compare ideas.

Earth Observation Challenge

10 апреля 2018 — 25 июля 2018
Осталось 2 месяца
These challenges are critical to understanding and measuring the impact of climate change and urban development in remote areas. To accelerate innovation in support of these global challenges, we’re opening up DigitalGlobe’s 100+ petabyte image library and geospatial big data platform, GBDX, along with ESA Sentinel Data. We’re looking for passionate participants who can leverage DigitalGlobe and ESA resources to build geospatial solutions supporting these initiatives. Participant teams will have two months to transform Earth imagery into meaningful context and actionable insight for sustainable global development, business growth, and geospatial intelligence.

Kaggle: Freesound General-Purpose Audio Tagging Challenge

29 марта 2018 — 1 августа 2018
Осталось 2 месяца, 1 неделя
You’re challenged to build a general-purpose automatic audio tagging system using a dataset of audio files covering a wide range of real-world environments. Sounds in the dataset include things like musical instruments, human sounds, domestic sounds, and animals from Freesound’s library, annotated using a vocabulary of more than 40 labels from Google’s AudioSet ontology. To succeed in this competition your systems will need to be able to recognize an increased number of sound events of very diverse nature, and to leverage subsets of training data featuring annotations of varying reliability (see Data section for more information).

Kaggle: TrackML Particle Tracking Challenge

1 мая 2018 — 14 августа 2018
Осталось 2 месяца, 3 недели
Specifically, in this competition, you’re challenged to build an algorithm that quickly reconstructs particle tracks from 3D points left in the silicon detectors. This challenge consists of two phases: The Accuracy phase will run on Kaggle from May to July 2018. Here we’ll be focusing on the highest score, irrespective of the evaluation time. This phase is an official IEEE WCCI competition (Rio de Janeiro, Jul 2018). The Throughput phase will run on Codalab from July to October 2018. Participants will submit their software which is evaluated by the platform. Incentive is on the throughput (or speed) of the evaluation while reaching a good score. This phase is an official NIPS competition (Montreal, Dec 2018).