Kaggle: Airbus Ship Detection Challenge

30 июля 2018 — 15 ноября 2018
Осталось 1 день, 16 часов
Airbus offers comprehensive maritime monitoring services by building a meaningful solution for wide coverage, fine details, intensive monitoring, premium reactivity and interpretation response. Combining its proprietary-data with highly-trained analysts, they help to support the maritime industry to increase knowledge, anticipate threats, trigger alerts, and improve efficiency at sea. A lot of work has been done over the last 10 years to automatically extract objects from satellite images with significative results but no effective operational effects. Now Airbus is turning to Kagglers to increase the accuracy and speed of automatic ship detection.

Kaggle: Google Analytics Customer Revenue Prediction

13 сентября 2018 — 16 ноября 2018
Осталось 2 дня, 16 часов
In this competition, you’re challenged to analyze a Google Merchandise Store (also known as GStore, where Google swag is sold) customer dataset to predict revenue per customer. Hopefully, the outcome will be more actionable operational changes and a better use of marketing budgets for those companies who choose to use data analysis on top of GA data.

Pommerman

21 мая 2018 — 21 ноября 2018
Осталось 1 неделя
Build an AI to Compete against the World.

Kaggle: Quick, Draw! Doodle Recognition Challenge

26 сентября 2018 — 5 декабря 2018
Осталось 3 недели
Your task is to build a better classifier for the existing Quick, Draw! dataset. By advancing models on this dataset, Kagglers can improve pattern recognition solutions more broadly. This will have an immediate impact on handwriting recognition and its robust applications in areas including OCR (Optical Character Recognition), ASR (Automatic Speech Recognition) & NLP (Natural Language Processing).

Kaggle: PLAsTiCC Astronomical Classification

29 сентября 2018 — 18 декабря 2018
Осталось 1 месяц
The Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC) asks Kagglers to help prepare to classify the data from this new survey. Competitors will classify astronomical sources that vary with time into different classes, scaling from a small training set to a very large test set of the type the LSST will discover.

crowdAI: AI-generated music challenge

1 января 2018 — 31 декабря 2018
Осталось 1 месяц, 2 недели
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. There are two special aspects of this challenge, apart from the extremely interesting application. First, the results of the models will be evaluated by humans, with an ELO-style system where volunteers are given two randomly paired pieces of generated music, and choose the one they like better. Second, the top five models will at the end each generate a piece of music that will be performed live on stage at the Applied Machine Learning Days!

Kaggle: Predict Future Sales

8 февраля 2018 — 2 января 2019
Осталось 1 месяц, 2 недели
This challenge serves as final project for the "How to win a data science competition" Coursera course. In this competition you will work with a challenging time-series dataset consisting of daily sales data, kindly provided by one of the largest Russian software firms - 1C Company.

Kaggle: Two Sigma Using News to Predict Stock Movements

25 сентября 2018 — 9 января 2019
Осталось 1 месяц, 3 недели
By analyzing news data to predict stock prices, Kagglers have a unique opportunity to advance the state of research in understanding the predictive power of the news. This power, if harnessed, could help predict financial outcomes and generate significant economic impact all over the world.

Kaggle: Human Protein Atlas Image Classification

4 октября 2018 — 11 января 2019
Осталось 1 месяц, 4 недели
In this competition, Kagglers will develop models capable of classifying mixed patterns of proteins in microscope images. The Human Protein Atlas will use these models to build a tool integrated with their smart-microscopy system to identify a protein's location(s) from a high-throughput image.

Kaggle: PUBG Finish Placement Prediction

5 октября 2018 — 31 января 2019
Осталось 2 месяца, 2 недели
The team at PUBG has made official game data available for the public to explore and scavenge outside of "The Blue Circle." This competition is not an official or affiliated PUBG site - Kaggle collected data made possible through the PUBG Developer API. You are given over 65,000 games' worth of anonymized player data, split into training and testing sets, and asked to predict final placement from final in-game stats and initial player ratings. What's the best strategy to win in PUBG? Should you sit in one spot and hide your way into victory, or do you need to be the top shot? Let's let the data do the talking!