https://github.com/raulmaulidhino-dev/ml_modelling_regression

There are many factors that influence the grades/scores of students. One of the factors is study hours. In this mini analysis project, there are 3 models that will learn and predict the relation between study hours of students and their scores in an exam/test. This project will result the best ML model to solve the problem.
https://github.com/raulmaulidhino-dev/ml_modelling_regression

data data-analysis-python data-science eda machine-learning scikit-learn

Last synced: 13 days ago
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There are many factors that influence the grades/scores of students. One of the factors is study hours. In this mini analysis project, there are 3 models that will learn and predict the relation between study hours of students and their scores in an exam/test. This project will result the best ML model to solve the problem.

• Host: GitHub
• URL: https://github.com/raulmaulidhino-dev/ml_modelling_regression
• Owner: raulmaulidhino-dev
• Created: 2024-08-16T11:34:37.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-09-15T03:59:49.000Z (4 months ago)
• Last Synced: 2024-11-03T03:43:04.097Z (2 months ago)
• Topics: data, data-analysis-python, data-science, eda, machine-learning, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 3.53 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ML_Modelling_Regression

There are many factors that influence the grades/scores of students. One of the factors is study hours. In this mini analysis project, there are 3 models that will learn and predict the relation between study hours of students and their scores in an exam/test. This project will result the best ML model to solve the problem. 

**Goals :**

-  Range of best number of study hours to get a high score

-  Minimum and maximum number of study hours that are good for learning

-  Range of study hours that are less suitable for getting good scores or grades

-  Finding the best Machine Learning model from [Scikit-learn](https://scikit-learn.org) library to predict and answer the three goals above

With this analysis, the students are able to find the perfect range of study hours for getting good scores.

**Insights :**

- Study Hours and Scores are strongly related

- Studying for 12 hours and above per day can increase the chances of getting high scores

- Approximately 4 hours of study time and 2 hours or less is the ideal time to study

**Advices :**

- Some students should not study for 3 hours, 6 hours, or 10 hours per day

- Because the dataset is still very small, which only amounts to 2 columns and 25 rows, the results of the conclusions obtained may not be valid or not representative of the existing sample

- The size of the dataset should be further expanded

For a more interactive explanation of the project, you can read and/or download this presentation on the repository files menu or [here](https://drive.google.com/drive/folders/1UTuSdZ-Li9S4rIOFBMjAXfCzkEq9D7YK).

If you have any suggestions or feedback, please don't hesitate to contact to me in direct message on [LinkedIn](https://linkedin.com/in/raulahmadm) or [Email](mailto:[email protected])