Aim:-This project aims to analyze data in detail on vaccinated people and fully vaccinated by year and country. Introduction:-The main objective of this project is to analyze the data on, COVID-19 Vaccinations. Through the Analysis of data, we can find out some important insights. Problem Statement:- • We can find…

Aim:-This project aims to collect and analyze the data of Trip Pricing with Taxi Mobility Analytics site data and analyze it in detail by each Destination type, Gender, Type of Cab and Customer Rating, trip destination, etc. on that site. Introduction:-The main objective of this project is to analyze the data on, Trip…

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A detailed insight on what can be the possible issues on gender gap in STEM Jobs: After analysing the main reason for gender gap in STEM jobs is women are showing intrest in health related fields like (biological sciences) and domination of men in these fields leads too the gap in STEM jobs gradually increasd from 2009,…

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https://docs.google.com/spreadsheets/d/1YPDm9Z0tFCTjI4qpNHaXQ8MngVtXpuCN/edit?usp=sharing&ouid=113425140896709226641&rtpof=true&sd=true

/*1. create a database*/create database ecommerce;/*3.RUN SQLCOMMAND TO SEE THE STRUCTURE OF TABLE*/use ecommerce;desc users_data;select*from users_data;/*4.RUN SQLCOMMAND TO SELECT FIRST 100 ROWS OF THE DATABASE*/select *from users_data limit 100;/*5.HOW MANY DISTINCT VALUES EXIST IN TABLE FOR FIELD COUNTRY AND LANGUAGE*/select…

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1.  The difference in the formula of variance for population and sample is due to the fact that we do not know the population mean in the case of a sample. In the case of a population, we can use the population mean to calculate the variance. This is because we know the value of the population mean, so we can subtract…

1.  a)The first business moment is the mean, which is the average of the values of X multiplied by their probabilities. The mean is calculated as follows: Mean = Σx*P(x) Mean = 0 * 0.35 + 1 * 0.25 + 2 * 0.15 + 3 * 0.15 + 4 * 0.10 Mean = 1.6 b)The second business moment is the variance, which is a measure…

1. This code first defines a function called gradient_descent() that takes in the input data (x), the target output (y), the learning rate, and the number of epochs. The function then performs gradient descent on the data and returns the final weights. The main function then creates the input data (x) and the…

1. Pros: High accuracy: SVMs are known for their high accuracy, especially in cases where the classes are well-separated. Robust to noise: SVMs are relatively robust to noise, which means that they can still perform well even if the data contains some errors. Scalable: SVMs can be scaled to large datasets…

1. import numpy as npimport pandas as pdfrom sklearn.neighbors import KNeighborsClassifierfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score, log_loss # Load the datasetdata = pd.read_csv(""C:\Users\venka\Downloads\Mechanical_datasets-20230715T140641Z-001.zip.csv",encoding="unicode_escape")…

1. A neural network is a type of machine learning algorithm that is inspired by the human brain. It is a collection of interconnected nodes that are arranged in layers. The nodes in each layer are connected to the nodes in the next layer, and so on. The nodes in a neural network are called neurons. Neural networks…

1.  There are a number of ways to calculate similarity if data is categorical in nature. Some of the most common methods include: Jaccard similarity: The Jaccard similarity coefficient is a measure of similarity between two sets. It is calculated by dividing the number of elements that are common to both sets…

Objective: In this project we are going to clean the dataset of '1985 Automobile Dataset'. About the Dataset: This is a raw dataset about cars in 1985. This data set consists of three types of entities:(a) the specification of an auto in terms of various characteristics,(b) its assigned insurance risk rating,(c) its…

Project_02:Implement Clustering and then predict the class of car from “Car dataset”. Attributes imformation: 1.symboling: -3, -2, -1, 0, 1, 2, 3 2.normalized-losses: continuous from 65 to 256 3.make: alfa-romero, audi, bmw, chevrolet, dodge, honda, isuzu, jaguar, mazda, mercedes-benz, mercury, mitsubishi,…

1. Insurance data is a type of "supervised data" . This means that the data is labeled, meaning that each data point has a known output value.   2. The minimum sample size n to get the 99% accurate predictions with a precision of 0.02 is approximately 326 individuals. The formula for calculating the minimum sample…

import pandas as pd # Step 1: Read the data for white and red wines into separate DataFrames white_wine_data = pd.read_csv('white_wine_data.csv') red_wine_data = pd.read_csv('red_wine_data.csv') print("White Wine Data:") print(white_wine_data.head()) print("\nRed Wine Data:") print(red_wine_data.head()) print("Size of…