Jovian
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Version 1
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import jovian
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#Sentimental analysis using python
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from textblob import TextBlob
import nltk
from newspaper import Article
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url='https://towardsdatascience.com/understanding-cv-how-ai-sees-our-world-a977b90bf612'
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article=Article(url)
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#doing some nlp
article.download()
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article.parse()
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nltk.download('punkt')
[nltk_data] Downloading package punkt to [nltk_data] C:\Users\poorna\AppData\Roaming\nltk_data... [nltk_data] Package punkt is already up-to-date!
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True
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article.nlp()
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#get the summary 
text=article.summary
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print(text)
Yann LeCun, famous for his work on the convolutional neural networks, applied back-propagation to the convolutional neural networks in 1989. Alex Krizhevsky, along with his AlexNet, won the ImageNet competition on September 30, demonstrated the superior performance of approaches based on convolutional neural networks. Advancing to Deep Learning: Convolutional Neural Networks & Residual Neural Networks“No one tells a child how to see, especially in the early years. Convolutional LayerConvolutional Layer (3x3)Convolutional Layer usually appears as the first layer of a Convolutional Neural Network. Neural Networks Makes Judgements Based on Textures, Image from Original PaperThe neural networks are also vulnerable to high-frequency disturbances.
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obj=TextBlob(text)
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sentiment=obj.sentiment.polarity
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print(sentiment)
0.13055555555555556
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if sentiment==0:
    print('The text is neutal')
elif sentiment>0:
    print("The text is positive")
else:
    print("The text is negative")
The text is positive
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jovian.commit()
[jovian] Saving notebook..
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