Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/anu-gtb/campus-placement


https://github.com/anu-gtb/campus-placement

campus-placement cassandra-database data-science jupyter-notebook logistic-regression machine-learning prediction-model streamlit webapp

Last synced: 23 days ago
JSON representation

Awesome Lists containing this project

README

        

# Campus-Placement
This is a Machine Learning-based prediction project in which the task is to predict whether a student may get placed or not on the basis of different academic factors.

Steps involved in implementation of this project are -:
1. Exploratory Data Analysis(EDA)
2. Data Preprocessing and Feature Extraction
3. Data Visualization
5. Model Training
6. Evaluation
7. API development
8. Deployment

Tools and Technologies used -:
1. Cassandra Database - For dataset

The dataset contains a total of 215 non-null rows and 15 columns.

2. Pandas - EDA
3. Scikit-Learn, Scipy and StatsModels - Data Preprocessing and Feature Extraction
4. Matplotlib and Seaborn - Data Visualization
5. Logistic Regression - Final model training(best model chosen)
6. Scikit-Learn Metrics - Evaluation
7. Streamlit - For User Interface development
8. Streamlit Cloud - Deployment

Database Link -: https://astra.datastax.com/org/0dd23226-b7a5-45db-9a1d-73ce17d26290/database/a5524767-c3d6-41f9-a8af-ff6043cfd45e/data-explorer

![front](https://github.com/anu-gtb/Campus-Placement/assets/140297541/2f15e333-29ac-4457-b17d-73a8b276d686)

On clicking submit button at bottom,

![submit](https://github.com/anu-gtb/Campus-Placement/assets/140297541/d325d2d7-a952-4606-bbde-532888c8de3f)

We get the output as Placed/Not Placed -:

![Screenshot (178)](https://github.com/anu-gtb/Campus-Placement/assets/140297541/30fb59ba-9cb0-4ca9-934c-954b15bc5a29)