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Student Well Beings

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by norochalise dot icon Updated: Nov 2, 2021

Solution Kit 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

Python doticonstar image 14197 doticonVersion:Currentdoticon
License: Permissive (BSD-3-Clause)

Jupyter metapackage for installation, docs and chat

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            jupyterby jupyter

            Python doticon star image 14197 doticonVersion:Currentdoticon License: Permissive (BSD-3-Clause)

            Jupyter metapackage for installation, docs and chat
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                      Data Mining

                      We used pandas and numpy for Data Mining.

                      pandasby pandas-dev

                      Python doticonstar image 37439 doticonVersion:v2.0.0rc1doticon
                      License: Permissive (BSD-3-Clause)

                      Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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                                pandasby pandas-dev

                                Python doticon star image 37439 doticonVersion:v2.0.0rc1doticon License: Permissive (BSD-3-Clause)

                                Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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                                          numpyby numpy

                                          Python doticonstar image 23036 doticonVersion:v1.24.2doticon
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                                          The fundamental package for scientific computing with Python.

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                                                    numpyby numpy

                                                    Python doticon star image 23036 doticonVersion:v1.24.2doticon License: Permissive (BSD-3-Clause)

                                                    The fundamental package for scientific computing with Python.
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                                                              Data Visualizations

                                                              We used matplotlib and seaborn python libraries for data visualizations.

                                                              matplotlibby matplotlib

                                                              Python doticonstar image 17111 doticonVersion:v3.7.1doticon
                                                              no licences License: No License (null)

                                                              matplotlib: plotting with Python

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                                                                        matplotlibby matplotlib

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                                                                        matplotlib: plotting with Python
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                                                                                  seabornby mwaskom

                                                                                  Python doticonstar image 10513 doticonVersion:v0.12.2doticon
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                                                                                  Statistical data visualization in Python

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                                                                                            seabornby mwaskom

                                                                                            Python doticon star image 10513 doticonVersion:v0.12.2doticon License: Permissive (BSD-3-Clause)

                                                                                            Statistical data visualization in Python
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                                                                                                      Machine learning

                                                                                                      We used Sklearn python libraries for binary classification problem solve.

                                                                                                      scikit-learnby scikit-learn

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                                                                                                      scikit-learn: machine learning in Python

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                                                                                                                scikit-learnby scikit-learn

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                                                                                                                scikit-learn: machine learning in Python
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                                                                                                                          Kit Solution Source

                                                                                                                          Student-well-beingsby norochalise

                                                                                                                          Jupyter Notebook doticonstar image 0 doticonVersion:Currentdoticon
                                                                                                                          License: Permissive (MIT)

                                                                                                                          Based on the students information we classify mental disorder and parent satisfactions. Both binary classifications problem we solved by traditional machine learning. algorithms.

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                                                                                                                                    Student-well-beingsby norochalise

                                                                                                                                    Jupyter Notebook doticon star image 0 doticonVersion:Currentdoticon License: Permissive (MIT)

                                                                                                                                    Based on the students information we classify mental disorder and parent satisfactions. Both binary classifications problem we solved by traditional machine learning. algorithms.
                                                                                                                                    Support
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                                                                                                                                              Deployment Information

                                                                                                                                              Our solution and all dependent assets are available in the below repository.

                                                                                                                                              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.

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