Here is a link to a small .csv file (first 1000 rows of my data) https://drive.google.com/file/d/1C7thFlOnDn-oTc6AaDWA3CXXcX8m9NRu
The idea is to cluster the recipe names into n-categories so that afterwards I can assign every recipe to a category. Of note, there are tags and ingredients for every recipe, maybe this information helps to refine the clusters? For example the algorithm (maybe a semantic analysis?) should output: categorised recipes into 200 biggest found categories: (hamburger, soup, pizza, ...)
Is there a way to do this?
Note: I have for every recipe min. 1 image. The idea is to label my images with n-categories, afterwards to train a convolutional neural network with my data. The input would be an food image, the output would be a category.