Dear Sir,       I have completed project1. please find the attachment below.

Dear Team,     i have completed SQL Project 1. Please,find the attachment below.

Dear Team,          I have completed Project 2. Please, Find the attachment below.

Dear Team,        I have completed SQL project 2. Please, Find the attachment below.

Dear Team,       I have completed Machine Learning Project 1. Please,find the attachment below.

1) Why there is a difference in the formula of variance for population and sample Ans:-Two Quantities that we are considering here .   PopulationVariance−σ²  SampleVariance−s²  Sample Variance of “n” samples from the Population is given by the below formula  …

Dear Team,     I have completed Project 2 . Find the attachment below.

Dear Team,  I have completed project 1. Please find the attachment below.

Dear Team,    I have completed Tableau project 2. Please, find the attachment below.

Dear Team,    I have completed project1. Please find the attachment below.

https://drive.google.com/drive/folders/1Nv2XIggLk0jwXiy9bL4XEOqO_EEEUNXJ?usp=sharing

1)Calculate all 4 business moments using pen and paper for the below data set? First business moment The first business moment is the measure of central tendency Mean or expected value, μ=∑x.P(x) For the data, we calculate the data as follows: μ=∑x.P(x)=1.4 Second business moment The second business moment…

Q1: Perform Gradient Descent in Python with any loss function. A1:  Gradient descent is an optimization technique that can find the minimum of an objective function. It is a greedy technique that finds the optimal solution by taking a step in the direction of the maximum rate of decrease of the…

  Pros and cons of SVM Support Vector Machines (SVMs) are a type of machine learning algorithm that can be used for classification or regression tasks. Here are some pros and cons of using SVM: Pros: 1. Effective in high-dimensional spaces: SVMs are particularly useful in situations where the number of features is…

KNN: K-Nearest Neighbors is a supervised machine learning algorithm that classifies a data point based on how its neighbors are classified. It classifies new cases based on feature similarity measures. KNN algorithm k in the KNN algorithm is a parameter that refers to the number of nearest neighbors to include in the majority…

1.What is a Neural Network? -- A neural network is a type of artificial intelligence model that is inspired by the structure and function of the human brain. It is a computational system that is composed of interconnected nodes or neurons that work together to process and analyze complex data. The neurons are organized…

1. How does similarity is calculated if data is categorical in nature   To measure similarity between categorical data in K-means, we can use a distance metric such as Jaccard distance or Hamming distance. Jaccard distance measures the dissimilarity between two binary vectors, where each element in the vector represents…

Data Cleaning on Automobile 1985 dataset and perform descriptive analytics:-  No. of data points: 205 Number of Attributes: 26 total -- 15 continuous -- 1 integer -- 10 nominal Attribute Information: | Attribute | Attribute Range -- symboling: -3, -2, -1, 0, 1, 2, 3-- normalized-losses: continuous from 65 to 256-- make:…

Implement Clustering and then predict the class of car from “Car dataset”? Importing Libraries: Reading the data and separating the target variables: Performing Standardization and One hot encoding and combining the data: Checking the converted data: Clustering using Kmeans: Tuning the model: Defining the best clusters:…