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README.md
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---
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language: en
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tags:
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-
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license: apache-2.0
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datasets:
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- surprise
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pbar.close()
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self.df = pd.DataFrame(df, columns = ['userID', 'itemID', 'rating'])
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###Limitations and bias
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In this model we have faced some obstacles that we had overcome, but some of those, by the nature of the project, couldn't be totally solved.
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Due the fact that our dataset was build it by ourselves, there was no interaction yet between a user and the dataset, therefore we don't have
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realistic ratings which made us have to generate a simulation, making the results less believable.
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---
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language: en
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tags:
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- Recommendation
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license: apache-2.0
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datasets:
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- surprise
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pbar.close()
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self.df = pd.DataFrame(df, columns = ['userID', 'itemID', 'rating'])
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```
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### Limitations and bias
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In this model we have faced some obstacles that we had overcome, but some of those, by the nature of the project, couldn't be totally solved.
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Due the fact that our dataset was build it by ourselves, there was no interaction yet between a user and the dataset, therefore we don't have
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realistic ratings which made us have to generate a simulation, making the results less believable.
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