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Thanks for this great example!
To help with cold start, I did some experiments with provisioned concurrency, lazy load the transformers module in sentiment and prime the sentiment method if the pr…
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How to user bert turkish sentiment cased model for calculating sentiment scores of sentences with more than 512 sequence length?
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I know we can do text classification as positive and negative as mentioned in below notebook. Is there any way to classify neutral sentiment also?
https://colab.research.google.com/github/google-re…
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### Introducing Uncharted: Sentiment Analysis Module
Uncharted, a powerful module within the Tredge ecosystem, brings you advanced sentiment analysis capabilities for analyzing company's quarterly …
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- I realized while annotating `POSITIVE`, `NEGATIVE` labels for `product_review` corpus, there are distinct sentences that carry positive intent and other with negative intent and some with neutral.
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### 1.3 sentiment analysis (10 points)
Sentiment analysis section of this script: [https://github.com/rebeccajohnson88/PPOL564_slides_activities/blob/main/activities/fall_22/solutions/08_textasdata…
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Why do I get sentiment scores of -5.0, -5.0 in the output txt file when I run your code?
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## TL;DR
When defining a pipeline's elements and testing it on a couple of sentences, the tests results are inconsistent. Some go smoothly, while some encounter the following **type error**:
`TypeEr…
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For example, look into how Sustainalytics calculates their risk scores. Then consider ways of developing our own equations or additional inputs (like sentiment).
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I want to use this model to convert an opinion to a vector somehow (or at least arrive at an approximation of that).
E.g. "I'm an atheist" and "I believe in god" should be polar opposites. "I hate…