Sorting Udemy Courses
-
Strategy
Python, Pandas, Scikit Learn, Scipy
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Design
Data Science, Measurement Problems,
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Tags
Business Problem
Within the Data Science category, various Udemy courses are requested to be ranked.
In this case;
- A ranking based on
Rating,CommentandPurchasenumbers as well as a ranking based on the averageweightof these factors - Bayesian Average Rating (BAR Score)
Furthermore, at the end of the study, a hybrid solution of all these approaches and a ranking approach is discussed.
Bayesian Average Rating (BAR Score)
Bayesian Average Rating calculates a weighted probabilistic average using the distributional information of the scores.
The Bayesian method applies the approach of using past information to make something in the future.
Dataset Info
product_sorting.csv
| Feature | Definition |
|---|---|
| course_name | Course name |
| purchase_count | Number of purchases |
| rating | Average rating point |
| comment_count | Number of comment |
| 5_point | 5-point rating vote number |
| 4_point | 4-point rating vote number |
| 3_point | 3-point rating vote number |
| 2_point | 2-point rating vote number |
| 1_point | 1-point rating vote number |
Requirements
pandas==1.4.3
scikit_learn==1.1.2
scipy==1.7.3
Files
01-user-time-weighted-product-score.ipynb - User & Time Weighted Product Score Calculation Notebook
02.1-sorting-udemy-courses.ipynb - Sorting Udemy Courses Notebook
02.2-sorting-imdb-movies.ipynb - Sorting IMDB Movies Notebook
03-sorting-reviews.ipynb - Sorting Reviews Notebook
04-amazon-rating-product-sorting-reviews.ipynb - Rating Product & Sorting Reviews in Amazon