demo / scikit_sentiment_classifier / 0.1.2

Scikit-Learn Sentiment Classifier Demo

Royalty Free
Demo of deployed scikit-learn model to classify IMBD movie reviews as positive (1) or negative (0).
No Tags
Python 3.x
API Calls - 63 Avg call duration - 10.30sec
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Run an Example

  "Sentiment": "Negative",
  "review": "This movie is a disaster within a disaster film. It is full of great action scenes, which are only meaningful if you throw away all sense of reality. Let's see, word to the wise, lava burns you; steam burns you. You can't stand next to lava. Diverting a minor lava flow is difficult, let alone a significant one. Scares me to think that some might actually believe what they saw in this movie.<br /><br />Even worse is the significant amount of talent that went into making this film. I mean the acting is actually very good. The effects are above average. Hard to believe somebody read the scripts for this and allowed all this talent to be wasted. I guess my suggestion would be that if this movie is about to start on TV look away! It is like a train wreck: it is so awful that once you know what is coming, you just have to watch. Look away and spend your time on more meaningful content."

Install and Use


Install the Algorithmia CLI client by running:

curl -sSLf | sh

Then authenticate by running:

algo auth
CLI Install Docs


algo run demo/scikit_sentiment_classifier/0.1.2 -d '<INPUT>' --timeout 300
CLI Docs