Updated: Jul 31, 2023
1-Click Kit 
This Predictive Analytics kit provides an analytical view of students’ performance in mathematics and predicts grades to be scored in the final test.
The key features of this solution are:
- Analysis of grades of students
- Visualisation of patterns
- Prediction of grade in the final test
Deployment Information
Student grade predictive analytics created using this kit are added in this section. The entire solution is available as a package to download from the source code repository.
- Download, extract and double-click kit installer file to install the kit. Ensure you extract the zip file before running it.
- After successful installation of the kit, press 'Y' to run the kit and execute cells in the notebook.
- To run the kit manually, press 'N' and locate the zip file 'student-grade-analytics.zip'.
- Extract the zip file and navigate to the directory 'student-grade-analytics'.
- Open the command prompt in the extracted directory 'student-grade-analytics' and run the command 'jupyter notebook'.
- Locate and open the 'Predictive Analytics on Student grades.ipynb' notebook from the Jupyter Notebook browser window.
- Execute cells in the notebook.
Click on the button below to download the solution and follow the deployment instructions to begin set-up. This 1-click kit has all the required dependencies and resources you may need to build your Predictive Analysis App.
For a detailed tutorial on installing & executing the solution as well as learning resources including training & certification opportunities, please visit the OpenWeaver Community
Development Environment
VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers. Jupyter Notebook is used for our development.
notebookby jupyter
10204 Version:v7.0.0b4Jupyter Interactive Notebook
notebookby jupyter
Jupyter Notebook 10204 Version:v7.0.0b4 License: Permissive (BSD-3-Clause)
Data Mining
Our solution integrates data from various sources, and we have used below libraries for exploring patterns in these data and understanding correlation between the features.
numpyby numpy
23755 Version:v1.25.0rc1The fundamental package for scientific computing with Python.
numpyby numpy
Python 23755 Version:v1.25.0rc1 License: Permissive (BSD-3-Clause)
pandasby pandas-dev
38689 Version:v2.0.2Flexible 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 38689 Version:v2.0.2 License: Permissive (BSD-3-Clause)
Data Visualisation
The patterns and relationships are identified by representing data visually and below libraries are used for that.
matplotlibby matplotlib
17559 Version:v3.7.1
License: No License (null)matplotlib: plotting with Python
matplotlibby matplotlib
Python 17559 Version:v3.7.1 License: No License
seabornby mwaskom
10797 Version:v0.12.2Statistical data visualization in Python
seabornby mwaskom
Python 10797 Version:v0.12.2 License: Permissive (BSD-3-Clause)
grafanaby grafana
55818 Version:v10.0.0-previewThe open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
grafanaby grafana
TypeScript 55818 Version:v10.0.0-preview License: Strong Copyleft (AGPL-3.0)
Machine learning
Below libraries and model collections helps to create the machine learning models for the core prediction of use case in our solution.
tensorflowby tensorflow
175562 Version:v2.13.0-rc1An Open Source Machine Learning Framework for Everyone
tensorflowby tensorflow
C++ 175562 Version:v2.13.0-rc1 License: Permissive (Apache-2.0)
scikit-learnby scikit-learn
54584 Version:1.2.2scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python 54584 Version:1.2.2 License: Permissive (BSD-3-Clause)
Kit Solution Source
student-grade-analyticsby kandi1clickkits
0 Version:v1.0.0Analyse academic and non-academic information of students and predict grades
student-grade-analyticsby kandi1clickkits
Jupyter Notebook 0 Version:v1.0.0 License: Permissive (Apache-2.0)
Support
If you need help using this kit, you may reach us at the OpenWeaver Community.