Project 1 - Data Cleaning and Transformation using Pivot table and Charts for the Report on requirement of Team Hiring

This dashboard empowers mission driven organizations to harness the power of data visualization for social change. Women are tracked away from science and mathematics throughout their education, limiting their training and options to go into these fields as adults. The data set contains the data of women graduated by years,…

Project 1) English dictionary app and Library Book Management system

 Implement and deploy CNN model in real-time using python on Fashion MNIST dataset

Project 2

Project 1  

Aim The aim of this project is to collect and analyze the data in detail of the Pickup point of the Airport and City Request id in Uber Request Data.   Introduction Uber provides the 2016 data. By using this data find out the demand and supply Analysis gap of the cab. The main objective of this project is to analyze…

Aim The aim of this project is to analyze the data in detail on vaccinated people and fully vaccinated people by country in 2021-2022 Introduction Since the start of the COVID-19 outbreak, WHO has worked with countries and areas in Different regions on public health measures to slow or stop the spread of the virus. Safe…

import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.cluster import KMeans from sklearn.manifold import TSNE from sklearn.linear_model import LinearRegression cardata = pd.read_csv('Cars_mileage.csv')  print(cardata) HP MPG VOL SP WT 0 49 53.700681 89 104.185353 28.762059 1 55 50.013401…

import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns   auto= pd.read_csv("auto_clean.csv") print(auto) symboling normalized-losses make aspiration num-of-doors \ 0 3 122 alfa-romero std two 1 3 122 alfa-romero std two 2 1 122 alfa-romero std two 3 2 164 audi std four 4 2 164…

1) How does similarity is calculated if data is categorical in nature Categorical data (also known as nominal data) has been studied for a long time in various contexts. However, computing similarity between categorical data instances is not straightforward owing to the fact that there is no explicit notion of ordering…

1) What is a Neural Network? Neural networks reflect the behavior of the human brain, allowing computer programs to recognize patterns and solve common problems in AI, machine learning, and deep learning. Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset…

1) Apply knn to the “Surface defects in stainless steel plates” and identify the difference KNN is a simple algorithm, based on the local minimum of the target function which is used to learn an unknown function of desired precision and accuracy. The algorithm also finds the neighborhood of an unknown input,…

1) Pros and cons of SVM SVM     1) SVM stands for support vector machines.SVM is simple and provides good accuracy with less computational power, SVM is also used for regression but is widely applied for classification projects. There are several hyperplanes possible to classify the data points, but the…

1) Perform Gradient Descent in Python with any loss function Gradient Descent Gradient Descent is an optimization algorithm used for minimizing the cost function in various machine learning algorithms. Gradient descent is an optimization algorithm that is commonly used to train machine learning models and neural networks.…

1)Calculate all 4 business moments using pen and paper for the below data set 1)  mean µ= ∑(x1) * p(x)             = 0*0.35+1*0.25+ 2*0.15 + 3*0.15 + 4*0.10             = 0 + 0.25 + 0.3 +0.45 +0.4        …

  1) Why there is a difference in the formula of variance for population and sample Ans:- The sample variance is an estimate of  σ2 and is very useful in situations where calculating the population variance would be too cumbersome. The only difference in the way sample variance is calculated is that…

This dashboard empowers mission driven organizations to harness the power of data visualization for social change. The data set talks about the literacy rates in Tamilnadu. It is distributed according to the cities and their ranks. It contains the population, as per the gender. This dashboard gives us the insight about…

Project 2 Excel file due to large file size the file is not uploaded.because of that, I submit the screenshot of each question.please accept the screenshot of the answer.

Project 1 - Data Cleaning and Transformation using Pivot table and Charts for the Report on requirement of Team Hiring

Create new schema as alumni  ANS:- 2) Import all .csv files into MySQL ANS:-   3) Run SQL command to see the structure of six tables ANS- DESC college_a_hs;DESC college_a_se;DESC college_a_sj;DESC college_b_hs;DESC college_b_se;DESC college_b_sj;   6) Perform data cleaning on table College_A_HS and store…

PROJECT 1 ECOMMERCE  USE ecommerce; -- Question 3DESC users_data; -- Question 4SELECT * FROM users_data LIMIT 100; -- QUestion 5SELECT COUNT(DISTINCT country)Distinct_value_country,COUNT(DISTINCT language)DIstinct_value_language FROM users_data; -- Question 6SELECT gender, SUM(socialNbFollowers)max_users FROM users_data…

1.Question¶ import pandas as pdimport numpy as np Customer_Detail=pd.read_csv('customer_details.csv')Customer_Policy=pd.read_csv('customer_policy_details.csv') Customer_Detail.columns=['Customer_id','Gender','Age','Driving Licence Present','Region Code','Previously Insured','Vehicle age','Vehicle Damage'] Customer_Policy.columns=['Customer_id','Annual…