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TextBlob Review

2

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Excellent

Revainrating 5 out of 5Β Β 
RatingΒ 
5.0
Artificial Intelligence, Conversational Intelligence

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Description of TextBlob

TextBlob is a Python (2 and 3) library for processing textual data that provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.

Reviews

Global ratings 2
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Type of review

Revainrating 5 out of 5

Using TextBlobb for sentiment extraction

I used textblobs to extract customer reviews from different domains like Amazon or Yelp in order improve my recommendation engine results with semantic information about customers' sentiments towards products they have reviewed before buying them! It's not easy at all using this tool but i managed it somehow by reading documentation carefully! The process of extracting user feedbacks was very slow due time consuming nature so you need lots patience when dealing whit these tools especially if u…

Pros
  • Its really helpful for sentiment analysis which is most important part while making recommendations engines.The way we can easily search keywords within our database,it helps us find related words easier than others do ! Great software!!! :)I suggest its good choice as well !! :D
Cons
  • Almost never

Revainrating 5 out of 5

Best Text Analytics Tool ever made - easily extracts info

I like how easy to use this software can be with just few lines of code! It's really fast when you start working in it without any experience at all. The only downside right now would probably come from its price tag which seems too high compared to other similar products available online or even free ones if they are open source. If your looking for an amazing text analytics tool then definitely try outTextblobs! A lot has been done already but still not enough features implemented yet so keep

Pros
  • Amazing user interface
  • Easy integration into wordpress websites, no coding required works great as WordPress plugin also.
  • Many ways we could integrate ML algorithms (CNNs) easily via TensorFlow Hub libraries such us VGG 16/19 etc., making them work seamlessly within GCP environment;
  • Very flexible way one should build models by loading preprocessed datasets directly onto GPU memory instead offloading everything manually through CLI commands every time ;)
Cons
  • Secret