├── 0. Latest News Classifier
    ├── 00. Raw dataset
    │   └── BBC
    │   │   ├── bbc-fulltext.zip
    │   │   └── bbc-fulltext
    │   │       └── bbc
    │   │           ├── business
    │   │               ├── 001.txt
    │   │               ├── 002.txt
    │   │               ├── 003.txt
    │   │               ├── 004.txt
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    │   │               ├── 007.txt
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    │   │           ├── entertainment
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    │   │           ├── politics
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    ├── 01. Dataset Creation
    │   ├── 01. Dataset Creation.R
    │   ├── 01. Dataset Creation.Rmd
    │   ├── 01. Dataset Creation.Rproj
    │   ├── 01._Dataset_Creation.md
    │   ├── Dataset.rda
    │   └── News_dataset.csv
    ├── 02. Exploratory Data Analysis
    │   ├── 02. Exploratory Data Analysis.ipynb
    │   └── News_dataset.pickle
    ├── 03. Feature Engineering
    │   ├── 03. Feature Engineering.ipynb
    │   └── Pickles
    │   │   ├── X_test.pickle
    │   │   ├── X_train.pickle
    │   │   ├── df.pickle
    │   │   ├── features_test.pickle
    │   │   ├── features_train.pickle
    │   │   ├── labels_test.pickle
    │   │   ├── labels_train.pickle
    │   │   ├── tfidf.pickle
    │   │   ├── y_test.pickle
    │   │   └── y_train.pickle
    ├── 04. Model Training
    │   ├── 04. Model Training.ipynb
    │   ├── 05. Baseline Classifier.ipynb
    │   ├── 06. MT - Random Forest.ipynb
    │   ├── 07. MT - SVM.ipynb
    │   ├── 08. MT - KNN.ipynb
    │   ├── 09. MT - MultinomialNB.ipynb
    │   ├── 10. MT - Multinomial LogReg.ipynb
    │   ├── 11. MT - GBM.ipynb
    │   ├── 12. Best Model Selection.ipynb
    │   ├── 13. Dimensionality Reduction Plots.ipynb
    │   ├── 14. Model Interpretation.ipynb
    │   ├── 15. Sample Articles.ipynb
    │   └── Models
    │   │   ├── best_gbc.pickle
    │   │   ├── best_knnc.pickle
    │   │   ├── best_lrc.pickle
    │   │   ├── best_mnbc.pickle
    │   │   ├── best_rfc.pickle
    │   │   ├── best_svc.pickle
    │   │   ├── df_models_gbc.pickle
    │   │   ├── df_models_knnc.pickle
    │   │   ├── df_models_lrc.pickle
    │   │   ├── df_models_mnbc.pickle
    │   │   ├── df_models_rfc.pickle
    │   │   └── df_models_svc.pickle
    ├── 05. News Scraping
    │   ├── 16. Web Scraping Intro.ipynb
    │   ├── 17. WS - El Pais.ipynb
    │   ├── 18. WS - The Guardian.ipynb
    │   ├── 19. WS - Daily Mail.ipynb
    │   └── 20. WS - The Mirror.ipynb
    ├── 06. App Creation
    │   ├── 21. News Classification App.ipynb
    │   └── dash-app-lnclass
    │   │   ├── Pickles
    │   │       ├── best_svc.pickle
    │   │       └── tfidf.pickle
    │   │   ├── Procfile
    │   │   ├── app.py
    │   │   ├── environment.yml
    │   │   ├── nltk.txt
    │   │   └── requirements.txt
    ├── 07. Annex - Installation
    │   └── README.md
    ├── 08. Annex - Deployment
    │   └── README.md
    ├── 09. Report
    │   ├── Images
    │   │   ├── Image1.png
    │   │   ├── Image2.png
    │   │   ├── Image3.png
    │   │   ├── Image4.png
    │   │   ├── Image5.png
    │   │   └── Image6.png
    │   └── Latest News Classifier.pdf
    └── 10. App Creation v2
    │   ├── 21b. News Classification App V2.ipynb
    │   └── dash-app-latnewclas
    │       ├── Pickles
    │           ├── best_svc.pickle
    │           └── tfidf.pickle
    │       ├── Procfile
    │       ├── app.py
    │       ├── environment.yml
    │       ├── nltk.txt
    │       └── requirements.txt
└── README.md


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