58 lines
1.9 KiB
Markdown
58 lines
1.9 KiB
Markdown
# Air Paradis Project - Sentiment Analysis
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This repository contains the notebooks and source code for the sentiment analysis project on tweets, carried out as part of the OpenClassrooms "Air Paradis" program.
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---
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## Business Context
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The goal is to predict whether a tweet, or a short written expression, is perceived as positive or negative, in the context of an airline company. The project is based on the public **Sentiment140** dataset.
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## Project Description
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The project aims to develop a complete sentiment analysis system, including:
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- Exploratory data analysis of text data,
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- Comparison of several classification models (classical, advanced, and state-of-the-art),
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- Deployment of a REST API exposing an advanced model (based on embeddings and LSTM),
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- Implementation of a CI/CD pipeline to automate testing and deployment,
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- Local hosting on a NAS server to ensure data sovereignty.
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## Repository Structure
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- `notebooks/`: analysis and modeling notebooks,
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- `deployment/`: API code, tests, Dockerfile and deployment-related files,
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- `docs/`: documentation and related materials,
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- `.github/workflows/`: CI/CD pipelines.
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---
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## Model Training
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Training phases were mainly conducted on Google Colab to leverage GPU resources required for deep learning models.
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---
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## Usage
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The notebooks detail the analysis and training steps. The API is available in `deployment/api`.
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## Notes
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- The `requirements.txt` files in `notebooks/` come from Google Colab environments and may contain dependencies that are not optimal for local use.
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- The `.env` file, excluded from the repository, contains the necessary environment variables.
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---
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This README will be updated progressively as the project advances.
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Some code comments can remain in french language (as well as the notebooks markdowns etc.). All will be changed into english in the future.
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---
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**Project completed as part of the OpenClassrooms "Data Scientist - Project 7" program**
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