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Tinny-Robot / AI-ML-Jupyter-Notebooks

A collection of Jupyter notebooks for AI and ML tasks. Explore, learn, and contribute to advance your skills in artificial intelligence and machine learning. #Hacktoberfest friendly!
MIT License
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Added Sentiment Analysis #8

Closed prernamittal closed 10 months ago

prernamittal commented 10 months ago

Description This pull request adds the SentimentAnalysis.ipynb Jupyter Notebook to the NLP folder in the repository. The notebook performs sentiment analysis on movie reviews using the IMDb dataset.

Changes Made Added SentimentAnalysis.ipynb to the NLP folder. Added IMDBDataset.csv to the datasets folder.

Related Issue Closes #7

@Tinny-Robot Kindly accept this PR under Hacktoberfest'23. Thanks!

Tinny-Robot commented 10 months ago

Hi @prernamittal,

Thank you for your contribution to our project. We appreciate your effort in submitting your pull request.

We noticed that there is a FileNotFoundError issue in your notebook. It seems that the file paths may not be correctly addressed. To ensure a smooth experience for users, please double-check and correct the file paths in your notebook.

Additionally, we encourage you to consider adding some form of visualization to your notebook. Visualizations can greatly enhance the understanding of data and results, making your notebook more informative and engaging. Whether it's graphs, charts, or plots related to your analysis, they can provide valuable insights to readers.

Once you've addressed the FileNotFoundError issue and added visualizations (if applicable), please let us know. We'll be happy to review your pull request again.

If you have any questions or need assistance with addressing the issue or adding visualizations, please feel free to ask. We're here to help.

Thank you for your contribution, and we look forward to seeing the improvements in your pull request!

Best regards, Tinny-Robot

prernamittal commented 10 months ago

@Tinny-Robot Thank you for the feedback! I have added the data visualizations, short descriptions under each heading for beginners and also corrected the path to the dataset in the repo.