SLIP20

Q.1 Write a Java Program to implement Factory Design pattern for operating system example

// Product interface
interface OperatingSystem {
    void displayInfo();
}

// Concrete Products
class Windows implements OperatingSystem {
    @Override
    public void displayInfo() {
        System.out.println("This is Windows Operating System.");
    }
}

class Linux implements OperatingSystem {
    @Override
    public void displayInfo() {
        System.out.println("This is Linux Operating System.");
    }
}

class MacOS implements OperatingSystem {
    @Override
    public void displayInfo() {
        System.out.println("This is macOS Operating System.");
    }
}

// Factory interface
interface OperatingSystemFactory {
    OperatingSystem createOperatingSystem();
}

// Concrete Factories
class WindowsFactory implements OperatingSystemFactory {
    @Override
    public OperatingSystem createOperatingSystem() {
        return new Windows();
    }
}

class LinuxFactory implements OperatingSystemFactory {
    @Override
    public OperatingSystem createOperatingSystem() {
        return new Linux();
    }
}

class MacOSFactory implements OperatingSystemFactory {
    @Override
    public OperatingSystem createOperatingSystem() {
        return new MacOS();
    }
}

// Client class

public class OperatingSystemClient {
    public static void main(String[] args) {
        // Using the Factory Design Pattern to create different operating systems
        OperatingSystemFactory windowsFactory = new WindowsFactory();
        OperatingSystem windowsOS = windowsFactory.createOperatingSystem();
        windowsOS.displayInfo();

        OperatingSystemFactory linuxFactory = new LinuxFactory();
        OperatingSystem linuxOS = linuxFactory.createOperatingSystem();
        linuxOS.displayInfo();

        OperatingSystemFactory macosFactory = new MacOSFactory();
        OperatingSystem macosOS = macosFactory.createOperatingSystem();
        macosOS.displayInfo();
    }
}

Q.2 Write a python program to implement Polynomial Regression for given dataset. Use position_sal.csv.

import pandas as pd
import numpy as np
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
data = pd.read_csv('./csv/position_sal.csv')
X = data[['Level']]
y = data['Salary']
poly_features = PolynomialFeatures(degree=4)  # You can adjust the degree as needed
X_poly = poly_features.fit_transform(X)
model = LinearRegression()
model.fit(X_poly, y)
y_pred = model.predict(X_poly)
plt.scatter(X, y, color='blue', label='Actual Data')
plt.plot(X, y_pred, color='red', label='Polynomial Regression')
plt.xlabel('Position Level')
plt.ylabel('Salary')
plt.title('Polynomial Regression')
plt.legend()
plt.show()

Q.3 Print below array elements using map: a. const fruits = ["apple", "banana", "cherry", “bat”] b. Only print fruits it should remove bat and print it

Paste the FruitsList.jsx In src Folder

import React from 'react';

const FruitsList = () => {
  const fruits = ["apple", "banana", "cherry", "bat"];

  // Filter out "bat" from the fruits array
  const filteredFruits = fruits.filter(fruit => fruit !== "bat");

  return (
    <div>
      <h1>Fruits List</h1>
      <ul>
        {filteredFruits.map((fruit, index) => (
          <li key={index}>{fruit}</li>
        ))}
      </ul>
    </div>
  );
};

export default FruitsList;