https://github.com/eloyekunle/student_intervention
Machine learning model to analyze students' performance and predict success likelihood.
https://github.com/eloyekunle/student_intervention
student-intervention udacity udacity-machine-learning-nanodegree udacity-nanodegree
Last synced: 4 months ago
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Machine learning model to analyze students' performance and predict success likelihood.
- Host: GitHub
- URL: https://github.com/eloyekunle/student_intervention
- Owner: eloyekunle
- Created: 2016-09-19T15:37:49.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2016-09-19T16:04:32.000Z (about 9 years ago)
- Last Synced: 2025-03-19T05:55:01.094Z (7 months ago)
- Topics: student-intervention, udacity, udacity-machine-learning-nanodegree, udacity-nanodegree
- Language: Jupyter Notebook
- Size: 23.4 KB
- Stars: 8
- Watchers: 2
- Forks: 3
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Project 2: Supervised Learning
## Building a Student Intervention System
### Install
This project requires **Python 2.7** and the following Python libraries installed:
- [NumPy](http://www.numpy.org/)
- [Pandas](http://pandas.pydata.org)
- [scikit-learn](http://scikit-learn.org/stable/)
You will also need to have software installed to run and execute an [iPython Notebook](http://ipython.org/notebook.html)
Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), a pre-packaged Python distribution that contains all of the necessary libraries and software for this project.
### Code
Template code is provided in the notebook `student_intervention.ipynb` notebook file. While some code has already been implemented to get you started, you will need to implement additional functionality when requested to successfully complete the project.
### Run
In a terminal or command window, navigate to the top-level project directory `student_intervention/` (that contains this README) and run one of the following commands:
```ipython notebook student_intervention.ipynb```
```jupyter notebook student_intervention.ipynb```
This will open the iPython Notebook software and project file in your browser.
## Data
The dataset used in this project is included as `student-data.csv`. This dataset has the following attributes:
- `school` : student's school (binary: "GP" or "MS")
- `sex` : student's sex (binary: "F" - female or "M" - male)
- `age` : student's age (numeric: from 15 to 22)
- `address` : student's home address type (binary: "U" - urban or "R" - rural)
- `famsize` : family size (binary: "LE3" - less or equal to 3 or "GT3" - greater than 3)
- `Pstatus` : parent's cohabitation status (binary: "T" - living together or "A" - apart)
- `Medu` : mother's education (numeric: 0 - none, 1 - primary education (4th grade), 2 - 5th to 9th grade, 3 - secondary education or 4 - higher education)
- `Fedu` : father's education (numeric: 0 - none, 1 - primary education (4th grade), 2 - 5th to 9th grade, 3 - secondary education or 4 - higher education)
- `Mjob` : mother's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
- `Fjob` : father's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
- `reason` : reason to choose this school (nominal: close to "home", school "reputation", "course" preference or "other")
- `guardian` : student's guardian (nominal: "mother", "father" or "other")
- `traveltime` : home to school travel time (numeric: 1 - <15 min., 2 - 15 to 30 min., 3 - 30 min. to 1 hour, or 4 - >1 hour)
- `studytime` : weekly study time (numeric: 1 - <2 hours, 2 - 2 to 5 hours, 3 - 5 to 10 hours, or 4 - >10 hours)
- `failures` : number of past class failures (numeric: n if 1<=n<3, else 4)
- `schoolsup` : extra educational support (binary: yes or no)
- `famsup` : family educational support (binary: yes or no)
- `paid` : extra paid classes within the course subject (Math or Portuguese) (binary: yes or no)
- `activities` : extra-curricular activities (binary: yes or no)
- `nursery` : attended nursery school (binary: yes or no)
- `higher` : wants to take higher education (binary: yes or no)
- `internet` : Internet access at home (binary: yes or no)
- `romantic` : with a romantic relationship (binary: yes or no)
- `famrel` : quality of family relationships (numeric: from 1 - very bad to 5 - excellent)
- `freetime` : free time after school (numeric: from 1 - very low to 5 - very high)
- `goout` : going out with friends (numeric: from 1 - very low to 5 - very high)
- `Dalc` : workday alcohol consumption (numeric: from 1 - very low to 5 - very high)
- `Walc` : weekend alcohol consumption (numeric: from 1 - very low to 5 - very high)
- `health` : current health status (numeric: from 1 - very bad to 5 - very good)
- `absences` : number of school absences (numeric: from 0 to 93)
- `passed` : did the student pass the final exam (binary: yes or no)