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Dinesh Kumar/Final_report_text_Sentiment_project(winter of code) #8

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Please correct the filename

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xprilion commented Jan 7, 2021

@Dineshkumar536 please follow the filename guidelines on the project readme.

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Dineshkumar536 commented Jan 7, 2021 via email

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xprilion commented Jan 7, 2021

@Dineshkumar536 Its still not correct nor has it been made to the right folder. Please follow the guidelines.

Comment on lines +1 to +4
<center><a href="https://winterofcode.com/"><img src="https://camo.githubusercontent.com/c73f77959233a8adb69f3dee7bbb3ba5e016f4239c7496c82538cc60c984f56e/68747470733a2f2f77696e7465726f66636f64652e636f6d2f7374617469632f6d656469612f6f72672d6c6f676f2e39333564376634382e706e67" alt="gsoc" height="50"/></a>
<a href="https://www.python.org/"><img src="https://www.python.org/static/community_logos/python-logo.png" height="45"/></a>
<a href="https://fury.gl/latest/community.html"><img src="https://raw.githubusercontent.com/divyake/Cysec-Hacktoberfest/dcc84465cfcff73981f8fcb5c8fe3b1710c007e1/assets/logo.svg" alt="DSC-IEM" height="45"/></a>
</center>
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Please remove these, the WoC team will take care of appropriate logos and other styling while putting the report website live

* The data span a period of more than 10 years, including all **~500,000 reviews** up to October 2012.
* It contains **huge** dataset due to this i have choosen this dataset for my project.
* images
<a href="https://ibb.co/26fcYVw"><img src="https://i.ibb.co/6ZfDJ92/dataset.jpg" alt="dataset" border="0" height="250" width="1000"></a>
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Use Markdown

* Then i transform it on train reviews as **reviews_train_tfidf=tfidf_model.transform(reviews_train)**.
* Then i used **WordCloud** to see **top 10 words** by importing Wordcloud in my model.
* images
<a href="https://ibb.co/G5V30Sj"><img src="https://i.ibb.co/MCR5s0L/top10-words.jpg" alt="top10-words" border="0" height="500" width="800"></a>
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Use Markdown

* From these three i have figureout one algorithm which will fit to my model.
* So on the basis of **parameters** and **accuracy** i choosed Naive Bayes for my model to train my model on it.
* images
<a href="https://imgbb.com/"><img src="https://i.ibb.co/30zykYJ/f1-scores.jpg" alt="f1-scores" border="0"></a>
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use Markdown

* For pre-check my model **frontend and backend** i deployed it on my local server, and it working efficiently and precisely.
* I have added feature of **prediction of sentiment** , **keywords extraction and showing** , **Polarity and Subjectivity** and **Summary**. these are some features which will comes up when we put sone text in my frontend and gives output after processing in backend.
* link of my web app
https://sentimentproject.herokuapp.com/
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use markdown linking if you want it to open on clicking link

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