Student Well Beings
by norochalise Updated: Nov 2, 2021
Solution Kit
Student well beings help us to predict mental disorder and parent satisfaction based on the the students information. Both are binary classification problem and we used to solved by traditional machine learning algorithms. This is the project from Team Neuron Fire.
Development Environment
We used Jupyter Notebooks by developing and debugging. Jupyter Notebook is a web based interactive environment often used for experiments.
jupyterby jupyter
Jupyter metapackage for installation, docs and chat
jupyterby jupyter
Python
14197
Version:Current
License: Permissive (BSD-3-Clause)
Data Mining
We used pandas and numpy for Data Mining.
pandasby pandas-dev
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandasby pandas-dev
Python
37439
Version:v2.0.0rc1
License: Permissive (BSD-3-Clause)
numpyby numpy
The fundamental package for scientific computing with Python.
numpyby numpy
Python
23036
Version:v1.24.2
License: Permissive (BSD-3-Clause)
Data Visualizations
We used matplotlib and seaborn python libraries for data visualizations.
matplotlibby matplotlib
matplotlib: plotting with Python
matplotlibby matplotlib
Python
17111
Version:v3.7.1
License: No License
seabornby mwaskom
Statistical data visualization in Python
seabornby mwaskom
Python
10513
Version:v0.12.2
License: Permissive (BSD-3-Clause)
Machine learning
We used Sklearn python libraries for binary classification problem solve.
scikit-learnby scikit-learn
scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python
53572
Version:1.2.2
License: Permissive (BSD-3-Clause)
Kit Solution Source
Student-well-beingsby norochalise
Based on the students information we classify mental disorder and parent satisfactions. Both binary classifications problem we solved by traditional machine learning. algorithms.
Student-well-beingsby norochalise
Jupyter Notebook
0
Version:Current
License: Permissive (MIT)
Deployment Information
The entire solution is available as a package to download and install from the source code repository. Prerequisite: Python3 Follow below instructions to download and deploy the solution. 1. Open Command Line Interface 2. Run the command 'git clone https://github.com/norochalise/Student-well-beings.git' to clone the repository 3. Run the command 'cd Student-well-beings' to change directory 4. Run the command 'pip install -r requirements.txt' to install all the dependencies 5. Run the command 'jupyter notebook' to open the Jupyter Notebook 6. Click 'mental_disorder-classification.ipynb' to open the notebook 7. Execute all the cells in the notebook 8. Same way open parent_satisfaction_classification.ipynb and Execute all the cells in the notebook If there're any challenges while installing dependencies, run the command below to upgrade pip and try again. python -m pip install --upgrade pip Some command can be different based on the OS so please consider it.