Cognitive_challengers (Challenge 1)
by mvneema10 Updated: Nov 1, 2021
These are the basic libraries that are used to build the entire project.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python 38499 Version:v2.0.2 License: Permissive (BSD-3-Clause)
The fundamental package for scientific computing with Python.
Python 23587 Version:v1.24.3 License: Permissive (BSD-3-Clause)
The project uses the Seaborn package to develop key insights as well as analyses.
Statistical data visualization in Python
Python 10737 Version:v0.12.2 License: Permissive (BSD-3-Clause)
The project uses Logistic Regression to develop the model for predicting Success Factors for the list of inputs. The model predicts based on the inputs provided by the user that the student will succeed or fail in the course module.
Logistic Regression is a Machine Learning classification algorithm that is used to predict the probability of a categorical dependent variable. In logistic regression, the dependent variable is a binary variable that contains data coded as 1 or 0
Python 0 Version:Current License: No License
Front End Application:
The project uses Flask, HTML, CSS for the Front End UI application.
The Python micro framework for building web applications.
Python 63073 Version:2.2.5 License: Permissive (BSD-3-Clause)