Predicts whether two questions or sentences are similar to each other. Helps in deduplication of questions asked in forums like Quora, Reddit etc. Uses NLP techniques to build features.
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
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├── data
│ ├── source <- The source data sets in case the source files are downloaded from source systems.
│ ├── raw <- The original, immutable data dump.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── external <- Data from third party sources.
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├── logs <- Logs generated when program is running
│
├── models <- Trained and serialized models, model predictions, model summaries, or vectorizers
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
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└── src <- Source code for use in this project.
├── __init__.py <- Makes src a Python module
├── app.py <- Initiator for flask app
├── exception.py <- Custom exception handler
├── logger.py <- Custom logger
├── utils.py <- Set of custom utilities functions
│
├── data <- Scripts to extract data and transform data
│ ├── data_ingestion.py
│ └── data_transformation.py
│
├── pipelines <- Scripts to train models and then use trained models to make
│ │ predictions
│ ├── train_pipeline.py
│ └── predict_pipeline.py
│
└── templates <- Web pages to host to take real time inputs and provide predictions
├── index.html
└── home.html
Project based on the cookiecutter data science project template. #cookiecutterdatascience