Campus Placement Prediction

Description

The Placement of students is one of the most important objective of an educational institution. Reputation and yearly admissions of an institution invariably depend on the placements it provides it students with. That is why all the institutions, arduously, strive to strengthen their placement department so as to improve their institution on a whole. Any assistance in this particular area will have a positive impact on an institution’s ability to place its students. This will always be helpful to both the students, as well as the institution.
## Objectives The aim of project is to predict whether the student will be recruited in campus placements or not based on the available factors in the dataset.

Life Cycle of Machine Learning Project

Life Cycle of implementing machine learning application.

• Gathering the Data
• Data Preparation
• Data Preprocessing
• Create Model
• Evaluate Model
• Deploy the model

Dataset

The Campus Recruitment Prediction (Course Project) Dataset BY QuantumAI has been used for this purpose, taken from the Kaggle*. link is below.

• dataset

🛠️ Requirements

• Python (Programming Language version 3.7+)
• Flask (Python Backend Framework)
• sklearn (Machine Learning Library)
• pandas (Python Library for Data operations)
• NumPy (Python Library for Numerical operations)
• VS code (IDE)
• Azure (Cloud platform)
  
  

How to run this code...

• Create virtual environment

 py -3 -m venv venv

• Activate the environment

 venv\Scripts\activate

• Install the packages

pip install -r requirements.txt

• Run the app

python app.py

• Enter valid values in all input boxes and hit Predict.

If you like this project, please do give the star. If you have any suggestions or issues, please drop me a message.

• Kaggle Dataset mentioned here has it's own permission of use, it has not any relationship with this project.