Context After being challenged many times by my girlfriend about who is the best to guess the painter, I decided to use the power of machine learning to defeat her. I gathered a collection of artworks of the 50 most influential artists of all time. I added a dataset with basic information retrieved from wikipedia. I planned to create a convolutional neural network to recognise the artists looking the colors used and the geometric patterns inside the pictures. Content This dataset contains three files: - **artists.csv**: dataset of information for each artist - **images.zip**: collection of images (full size), divided in folders and sequentially numbered - **resized.zip**: same collection but images have been resized and extracted from folder structure Use *resized.zip* allows you to download less data and process faster your model. Acknowledgements The data was scraped from [artchallenge.ru][1] during the end of February 2019. Inspiration My goal is to create a model that learn to identify the artist analysing new pictures. I hope to learn new techniques from public kernels or see some interesting usage of this data. [1]: http://artchallenge.ru/?lang=en