Implement zero-shot learning on text to predict semantic relationships
$30-250 USD
着払い
I have triples such as:
(Justin - likes - apples)
(apples - color - red)
I would like to train such data using zero-shot learning to build a model to predict the relationship (second term in the triple). Zero-shot model known for the ability to predict objects that do not exist in the training set and that is what I want. For example, given the triple (man - .... - USA) the model should predict (lives) even if the relationship (lives) did not appear in the training data.
All the code should be using Python3.
プロジェクトID: #18309196
プロジェクトについて
8人のフリーランサーが、平均$237 で、この仕事に入札しています。
I am expert who understands the value of time. I pride myself in my attention to detail. I am very hard working and aim to deliver in less time than quoted. I want to make you, my employer happy without changing my bid もっと
Hi, I am interested in your project. I am Python and Machine Learning specialist, certified by Freelancer. I fully understand your requirements and I am sure I can help you. Let's discuss details by chat. Thank you.
Dear sir. Your project attracted my attention at first glance, because I've extensive experience in Predicting Semantic Relations Programming. I'm really confident about your project, and very eager to join your proj もっと
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