Application-classifier

Application Classifier is filter the data of all eligible candidates for cloud counselage pvt. ltd. internship program.

Analysis Module :

In this module I have Analyse the data using MatplotLib.

Program Files of analysis are as follows:

1. Visualization.py :: It is a python file which create a pdf of analysis graphs.
2. students.ipynb :: It is jupyter notebook file of program.

Some graphs are as follows:

1. No. of students applied for different technologies

2. Year-wise and area of study wise classification of students

3. Students who appied for data Science (knows python and don't know python)

Classification module :

In classification module I have used Support vector clustering Algorithm to classify and predict the data. svc :: SVC is a nonparametric clustering algorithm that does not make any assumption on the number or shape of the clusters in the data. In our experience it works best for low-dimensional data, so if your data is high-dimensional, a preprocessing step, e.g. using principal component analysis, is usually required. Several enhancements of the original algorithm were proposed that provide specialized algorithms for computing the clusters by only computing a subset of the edges in the adjacency matrix.

Program Files of Classification are as follows:

1. Appication-classifier.py :: A python file.
2. classifier.ipynb :: It is jupyter notebook file of program.

Classification Report ::

This Module has accurracy score of more than 91%. the detail report is in the image below ::