Kaggle Cdiscounts Image Classification Challenge Pavel Ostyakov, Alexey Kharlamov

Pavel Ostyakov and Alexey Kharlamov share their solution of Kaggle Cdiscount’s Image Classification Challenge. In this competition, Kagglers were challenged to build a model that classifies the products based on their images. From this video you will learn: - How to decide which architectures to use - How to train networks faster - Problem with training second layer of classifiers - Errors while solving the problem - Ideas of other teams: using several images of product, ensembling and using kNN Павел Остяков и Алексей Харламов рассказывают про задачу классификации товаров по изображениям (Kaggle Cdiscount’s Image Classification Challenge). Павел и Алексей вместе со своей командой заняли в соревновании 5 место. Из видео вы сможете узнать: - Как принимается решение, какие архитектуры использовать - Способы ускорить обучение сетей - Сложности построения второго слоя классификаторов и способ решения - Ошибки, допущенные в процессе решения - Идеи других участников: использование нескольких изображений товара, ансамблирование и kNN Yandex hosts biweekly training sessions on machine learning. These meetings offer an opportunity for the participants of data analysis contests to meet, talk, and exchange experience. Each of these events is made up of a practical session and a report. The problems are taken from Kaggle and similar platforms. The reports are given by successful participants of recent contests, who share their strategies and talk about the techniques used by their competitors. On Dec. 9, we looked at Porto Seguro’s Safe Driver Prediction challenge on Kaggle.