https://github.com/iamsauravsharma/insincere-question-classification
Insincere Question Classification project for final year
https://github.com/iamsauravsharma/insincere-question-classification
classification deep-learning insincere-questions jupyter jupyter-notebook machine-learning natural-language-processing python
Last synced: 6 months ago
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Insincere Question Classification project for final year
- Host: GitHub
- URL: https://github.com/iamsauravsharma/insincere-question-classification
- Owner: iamsauravsharma
- License: mit
- Created: 2019-01-10T12:13:09.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-11-10T15:11:31.000Z (over 1 year ago)
- Last Synced: 2023-11-10T16:29:15.773Z (over 1 year ago)
- Topics: classification, deep-learning, insincere-questions, jupyter, jupyter-notebook, machine-learning, natural-language-processing, python
- Language: Jupyter Notebook
- Size: 2.83 MB
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# INSINCERE_QUESTION_CLASSIFICATION
This is a final-year project done by a group of Bishal Gaire, Bishal Rijal, Dilip Gautam and Saurav Sharma. This project classifies whether a question is sincere or insincere using deep learning. It uses [dataset][dataset_link] provided by Kaggle.
**Project Info:**
| License | LoC |
| :---: | :---: |
| [![License: MIT][license_badge]][license_link] | [![LoC][loc_badge]][loc_link] |
**Install**
To install a project Poetry should be installed for package management. You can learn about poetry by visiting their [Github][github_link] or [Website][website_link].
**Running Locally**
This project is built using Google Colab free service so to run locally initially kaggle.json file is required. The steps for installing and authenticating a kaggle CLI can be found [here][kaggle_link].
All Jupyter Notebook files have two initial cells which are used for uploading a kaggle.json file on Google Colab so those initial two cells should be ignored while running locally.
Also, you are not required to run cells that installs a package using the pip command over Google Collab where packages are not preinstalled. All packages can be preinstalled using a poetry locally.
Similarly, a Python file is also present which is built from a jupyter notebook by removing unnecessary code cells from it but kaggle dataset needs to be downloaded early
You need trained model file and tokenizer file to run a Flask app or which can be generated running a Python file named `train_and_save_model.py` for running and training ANN and saving the best model. Initially models folder needs to be created otherwise it may fail to save a model altogether
**Running Over Google Colab**
To run Jupyter Notebook over Google Colab you need to have a kaggle.json file locally. While using Google Collab all cells are required.
To open the notebook in Google Colab you can replace out https://github.com address with https://colab.research.google.com/github or simply install [chrome extension][chrome_link] or [firefox extension][firefox_link].
You can find out more information about opening a GitHub link in Google Collab and other functionality [here][colab_github_demo_link]
**Other Models**
Other models which are tested are also present in different-models branch if you need to see models then you can see them in that branch and run as required. Only the Jupyter Notebook is available for those models.
**Images**
Images such as word cloud, bar and other diagrams are present in the images directory to visualize data length & and distribution.
**Research Paper**
We have also published our research paper on the project if you need to read our research paper and learn about the project then you can read out [research paper](research_paper.pdf) present in this repo.
[dataset_link]: https://www.kaggle.com/c/quora-insincere-questions-classification/data
[license_badge]: https://img.shields.io/github/license/iamsauravsharma/insincere-question-classification.svg
[license_link]: LICENSE
[loc_badge]: https://tokei.rs/b1/github/iamsauravsharma/insincere-question-classification
[loc_link]: https://github.com/iamsauravsharma/insincere-question-classification
[github_link]: https://github.com/sdispater/poetry
[website_link]: https://poetry.eustace.io/
[poetry_docs_link]: https://poetry.eustace.io/docs/
[kaggle_link]: https://www.kaggle.com/docs/api#getting-started-installation-&-authentication
[chrome_link]: https://chrome.google.com/webstore/detail/open-in-colab/iogfkhleblhcpcekbiedikdehleodpjo
[firefox_link]: https://addons.mozilla.org/en-US/firefox/addon/open-in-colab/
[colab_github_demo_link]: https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb