In this video we go through a bit more in depth into custom datasets and implement more advanced functions for dealing with text. Specifically we’re looking at a image captioning dataset (Flickr8k data set) with an image and a corresponding caption text that describes what’s going on in the image. I think the general principles from this video can be utilized to any project you’re working with when dealing with text data be it either translation, question answering, sentiment analysis etc. I also recommend taking a look at my Torchtext which can also be quite helpful and simplify the data loading process.

Flickr8k Dataset used in the video:

https://www.kaggle.com/dataset/e1cd22…

Github repository:

https://github.com/AladdinPerzon/Mach…

OUTLINE:

0:00 - Introduction

2:05 - Overview of what we’re going to do

4:05 - Imports

5:20 - Setup of Pytorch Dataset for loading Flickr

11:50 - Setup of Vocabulary and Numericalization

22:19 - Creating Collate for Padding of Batch

25:20 - Function for getting data loader

29:15 - Running code & fixing couple of errors

33:09 - Ending

#pytorch