Basics of ML & AL Week 2 Challenge

PROJECT 2 SUMMARY :  This summary provides a comprehensive overview of the analysis steps. It highlights the data loading, cleaning, analysis techniques (correlation, regression, groupby), and key findings about wine quality, alcohol content, acidity, and color. Data Acquisition and Exploration: Import Libraries:…

STATISTICS & PROBABILITY FOR DATA SCIENCES :PROJECT 1 PROBLEM STATEMENT - Assume that you have a dataset named "insurance.csv" containing information about insurance charges, including variables such as age, sex, BMI, number of children, smoking status, and region. Use Python with libraries like pandas, scikit-learn,…

AIM: 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,…

Q1.Difference in the formula of variance for Population and Sample : Variance - It is a way to measure spread of values in a dataset. Population Variance - Population variance is a type of variance that is used to determine the variability of the population data with respect to the mean. Sample Variance - Sample…

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. Overview: Importing the necessary libraries and the raw data. Renaming the columns. Finding the missing values. Filling the missing values. Exporting the data into a new…

Que1. How does similarity is calculated if data is categorical in nature Ans.   Hamming Distance: Hamming distance measures the number of positions at which the corresponding symbols in two strings are different. It is primarily used for strings of equal length, where each position represents a categorical attribute.…

1. Pros and cons of SVM. Ans. Support Vector Machines (SVM) are a type of supervised machine learning algorithm that can be used for classification or regression tasks. Here are some pros and cons of SVM: Pros: Effective in High-Dimensional Spaces: SVMs perform well even in high-dimensional spaces, making…

  Que. 1 Perform Gradient Descent in Python with any loss function Ans. Gradient descent is an optimization algorithm used to minimize a loss function in the context of machine learning. A simple example of gradient descent in Python using a quadratic loss function is given; In this example, I defined a simple…

  1)Calculate all 4 business moments using pen and paper for the below data set? Ans. I have attached a pdf file . 2)What is the significance of expected value when simple mean (Sum of all observations/number of observations) is already in place? Ans. A) Expected value: It is the Probability of an event multiplied by the…

1.Apply knn to the “Surface defects in stainless steel plates” and identify the differences Ans. I applied the KNN model to the  “Surface defects in stainless steel plates” dataset & attached a python file. 2. What are the pros and cons of knn ? Ans. KNN: K-Nearest Neighbors…

1. What is a Neural Network? Ans: A neural network is a computational model inspired by the human brain. It consists of interconnected nodes organized in layers, including input, hidden, and output layers. During training, the network learns to adjust weights and biases to make accurate predictions or classifications.…

Apply all five different machine learning models Logistic Regression, K-Nearest Neighbours Classifier, Support Vector machine, Decision Tree Classifier, Random Forest Classifier onthe given dataset. Ans.  Based on the provided model accuracies, here are some conclusions: K-Nearest Neighbors (KNN): Highest Accuracy:…

Problem Statement : Assume you are appointed as a Data scientist in any international humanitarian NGO, after the recent funding programmes, have been able to raise around $ 120 million. Now the CEO of the NGO call you to choose how to use this money strategically and effectively. The significant issues that comes while…

Project 2 - Supply and Demand Gap Analysis UBER Supply and Demand Gap Analysis Aim – The aim of this is project is to identify and analyze the gap in supply and demand of uber cabs having two pickup points namely airport and city from the dataset downloaded from kaggle. Dataset: https://www.kaggle.com/code/hellbuoy/uber-supply-demand-gap…

Project 1 - COVID-19 Vaccinations Trend Analysis Aim:-This Project mainly aims to find out the trend of the vaccinations around the world for the prevention of the Covid 19 pandemic and how much has been achieved so far. Introduction –The COVID 19 pandemic caused due to the Corona virus devastated the world by causing…

Project 2

a.Formatting of the data with using borders, font size and appropriate alignment of the content Dpne!. b. Screenshot is attached.  

Project 2 of Tableau !

A pie graph of women inBiological ScientistsChemists & Materials ScientistsComputer & Mathematical OccupationsEngineers & Architects The trend of percent women graduating in Computer science and Engineering from 2000-2015 A bar graph of what percent of women are in stem jobs by education in which field. cross…

PROJECT 2 

SQL Project completed..!

Project 2 - EDA on Vehicle Insurance Customer Data using Python Programming Language & its Libraries

There are two projects First English Dictionary App & Library Book Management System written in Python language.