https://github.com/samaalharbi2/virtual-work-experience---data-analysis-at-stc
Virtual Work Experience in Data Analysis at STC
https://github.com/samaalharbi2/virtual-work-experience---data-analysis-at-stc
analysis data data-visualization misk stc
Last synced: about 1 year ago
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Virtual Work Experience in Data Analysis at STC
- Host: GitHub
- URL: https://github.com/samaalharbi2/virtual-work-experience---data-analysis-at-stc
- Owner: samaalharbi2
- Created: 2025-02-18T11:41:47.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-25T17:22:07.000Z (over 1 year ago)
- Last Synced: 2025-04-05T22:34:59.661Z (over 1 year ago)
- Topics: analysis, data, data-visualization, misk, stc
- Language: Jupyter Notebook
- Homepage:
- Size: 577 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 Virtual Work Experience - Data Analysis at STC
## 🔍 Project Overview
This project is part of the **Virtual Work Experience in Data Analysis at STC**. The goal is to analyze **user behavior** on the STC TV platform and build models to improve content recommendations.
## 📂 Files in this Repository
- `Copy_of_stc_TV_T2.ipynb` → Data preprocessing & exploratory analysis.
- `Sama_Alharbi_stc_TV_T1.ipynb` → Initial analysis & visualization.
- `sama_stc_TV_T3.ipynb` → Model training & evaluation.
- `stc TV Data Set_T2.xlsx` → Dataset containing user viewing details.
## 🛠 Technologies Used
- **Python** (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn)
- **Jupyter Notebook** for interactive data analysis.
## 🔑 Key Insights
- **Users watch non-HD content longer than HD content.**
- **Recommendation models effectively predict user preferences.**
- **Further analysis can improve accuracy using demographic data.**