This is the second official project of the Udacity Machine Learning Nanodegree, and the course is co-created with Kaggle. In this project, we are going to build a supervised learning model to predict the student intervention necessity. The objective is to learn about the basic concepts of supervised learning and have a implementation practice on it.
README.mdstudent-data.csvstudent_intervention.htmlstudent_intervention.ipynb
In case you are new to Python and you do not know how to create an environment and install the package, here are few links that could help.
- Start your the terminal or command line
- Activate your environment
- Navigate to the root directory of this repository (./Building_a_Student_Intervention_System_Project/)
- Run
jupyter notebook student_intervention.ipynb
Then the web browser would open the jupyter notebook.
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)