README.md

Salary-Predictor-in-Interview--SVR

"Salary-Predictor-in-Interview-SVR" is a GitHub repository featuring a Support Vector Regression (SVR) model to predict salaries based on interview data. It includes data preprocessing, model training, and evaluation scripts for accurate salary prediction.

API deployment

from flask_cors import CORS
from flask import Flask, jsonify
import joblib
import numpy as np

app = Flask(__name__)
CORS(app)
# Load the model and scalers
model = joblib.load('SVM_Salary.pkl')
sc_X = joblib.load('sc_X.pkl')
sc_Y = joblib.load('sc_Y.pkl')

@app.route('/')
def home():
    return "Welcome to the SVR Model Prediction API!"

@app.route('/predict/<float:feature>', methods=['GET'])
def predict(feature):
    # Preprocess the data
    features_transformed = sc_X.transform(np.array([[feature]]))

    # Make prediction
    prediction = model.predict(features_transformed)

    # Inverse transform to original scale
    prediction_original_scale = sc_Y.inverse_transform(prediction.reshape(-1, 1))

    # Return the result as a JSON response
    return jsonify({'prediction': prediction_original_scale[0, 0]})

if __name__ == '__main__':
    app.run(debug=True)

Angular Application

Install flask dependencies

Prerequisites

• Python 3.6 or higher
• pip (Python package installer)

Installation

1. Clone the repository

   git clone https://github.com/your-username/your-repository.git
   cd your-repository
   python -m venv venv
   pip install -r requirements.txt
   pip install Flask flask_cors joblib numpy