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Just wondering if you could provide more details on your model like do you use a CNN or an LSTM? Is there a paper you have written about it? Also how do you get
by vinni2 8y ago
Just wondering if you could provide more details on your model like do you use a CNN or an LSTM? Is there a paper you have written about it? Also how do you get the data for training your models? Also do you do any retraining as new data comes in? Do you also have some groundtruth to measure the performance of your models?
- jdh30 8y agoI just noticed your post (https://news.ycombinator.com/item?id=18050422 https://news.ycombinator.com/item?id=18050422) about courses but cannot comment on it because it is too old. I am an employer with strong opinions. If you'd like to hear them please e-mail me here: https://www.idtechex.com/contact/team/dr_jon_harrop.asp https://www.idtechex.com/contact/team/dr_jon_harrop.asp
- jedwhite 8y agoThanks, there is a little more information in my reply to abrichr above. But in short, there are a large number of predictions run on each piece of content, and they each use different approaches - including traditional statistical models and ML, off-the-shelf APIs, as well as custom deep learning models we've developed through experimentation. So there's an evolving mix of models using different approaches (including CNNs, LSTM-like approaches / word2vec and some topic modelling using a doc2vec-style approach). It's still very much experimental though, and some predictions are way better than others! I'd love to do an arxiv.org paper or mlconf presentation down the track, as I think we have some interesting work here and I have an academic interest in the field, but it's way too early. In essence, we're working this out as we go to "make the thing" as practitioners first based on some unique insights, rather than it being a product derived from research first. [Edits for typos/clarity]