TECH SAKHA

All Dataset files= HERE Experiment 1 Copy Code 1 Exp 1: Write a Program to predict the price of the Uber ride from a given pickup point to the agreed drop-off location import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt train_data = pd.read_csv('/content/drive/MyDrive/ML Lab Sem 7/uber.csv') train_data.head(2) train_data.drop(labels='Unnamed: 0',axis=1,inplace=True) train_data.drop(labels='key',axis=1,inplace=True) train_data.info() train_data['pickup_datetime'] = pd.to_datetime(train_data['pickup_datetime'],errors='coerce') train_data.info() train_data.isnull().sum() # to check no of null values train_data.dropna(axis = 0, inplace= True) train_data.isnull().sum() train_data["pickup_latitude"].max() min_longitude = -180 max_longitude = 180 min_latitude = -90 max_latitude = 90 invalid_rows = train_data[ (train_data["dropoff_latitude...

all files= Experiment 1 Copy Code 1 package experiment; public class Exp1 { public static void main(String[] args) { if (args.length == 0) { System.out.println("Please provide some numbers as command-line arguments."); return; } double sum = 0; int validCount = 0; for (int i = 0; i Experiment 2 Copy Code 2 package experiment; public class Exp2 { public static void main(String[] args) { // 1. Widening Type Casting (Implicit Casting) int intValue = 100; long longValue = intValue; float floatValue = longValue; System.out.println("Widening Casting (Implicit):"); System.out.println("int to long: " + longValue); System.out.println("long to float: " + floatValue); // 2. Narrowing Type Casting (Explicit Casting) double doubleValue = 99.99; ...