Abhishek-Mallick / Abhishek-Mallick/universal-box

[TEMPLATE] - Sentiment Analysis - DataScience

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Vorherrschende Sprache
JavaScript
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Beschreibung

### What domain will the project template be based on?

Data Science

### If 'Others', please specify the preferred domain.

_No response_

### Particular directory path for the template.

`templates/Data-Science/NLP/Sentiment-Analysis/`

### What tech stacks do you want to include?

Python, NLTK, TextBlob

### Brief Description

A template for performing sentiment analysis on social media posts or product reviews. The project will utilize NLP techniques to classify sentiments as positive, negative, or neutral.

Note : A Jupyter notebook in form of a collab notebook should be linked in the README.md, and a user-friendly UI should be built using Flask or Streamlit.

### 👀 Have you spent some time checking if this issue has been raised before?

- [X] Yes
- [ ] No

### 🏢 Have you read the Code of Conduct?

- [X] I have read the [Code of Conduct](https://github.com/Abhishek-Mallick/universal-box/blob/main/.github/CODE_OF_CONDUCT.md)

### Would you like to work on this issue?

No

Beitragsleitfaden

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Rechercherichtung

Create a project template under templates/Data-Science/NLP/Sentiment-Analysis/. Include a Jupyter notebook for analysis, a Flask or Streamlit UI, and a README linking to the notebook. Check existing templates in the repository for structure and required files. Ensure the template demonstrates sentiment classification using NLTK and TextBlob on sample text data.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
flask, jupyter-notebook, python, streamlit
Bereich
ai, data, documentation, machine-learning, web-dev
Issue-Typ
Dokumentation
Schwierigkeit
3/5
Geschätzter Aufwand
1-2 Tage
Aktivitätsstatus
Veraltet
Klarheit
Klar beschrieben
Anfängerfreundlichkeit
65/100

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