oxford-cs-deepnlp-2017 / practical-2 Goto Github PK

I would like to use the TED talk dataset for research purposes. What will be a good place to access the data. Also are there any related publications which use this data?

Can you guys put this link inside the practical?

http://www.clg.ox.ac.uk/tedcorpus

Hello,

My name is Quei-An, an Msc student. For the first question of practical 2, I don't understand much what "starting from random embeddings" means. You mention GloVe afterwards, so I suppose that stands for word embeddings, but how can we train all word embeddings with such limited amount of data (only ~2000 talks)?

I tried somehow to implement the model with respect to the classification problem, but firstly I can only feed in one input at a time because each document has different size (number of words), secondly there's so little data that the accuracy turns out to be so poor. Then you mention "Training in batches", so I start getting confused.

Could you please clarify?

If I use fixed word representations (e.g. word2vec) then everything seems OK, I get about 56% accuracy by trying different hyperparameters.

Thank you and have a nice weekend.

I implemented the most basic neural net (following the instructions) and it is not performing very well.
I'm using Bag of Means to do document embedding which uses a Word2Vec model trained on the ted text.

I suspect that I have some sort of bug, as I'm a beginner with PyTorch. If the instructors don't mind, I'd like to share my code: [removed]
It is mostly modeled off this tutorial.