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A F&B manager wants to determine whether there is any significant difference in the diameter of the cutlet between two units. A randomly selected sample of cutlets was collected from both units and…
A hospital wants to determine whether there is any difference in the average Turn Around Time (TAT) of reports of the laboratories on their preferred list. They collected a random sample and record…
Sales of products in four different regions is tabulated for males and females. Find if male-female buyer rations are similar across regions.
Assignment-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and s…
Perform clustering (hierarchical) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontains inf…
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
Perform clustering (K means clustering) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontai…
Perform Clustering for the crime data and identify the number of clusters formed and draw inferences. Data Description: Murder -- Muder rates in different places of United States Assualt- Assualt r…
Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python.
Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of …
Apriori Algorithm Association rules with 10% Support and 70% confidence Association rules with 5% Support and 90% confidence Lift Ratio > 1 is a good influential rule in selecting the associated tr…
Association-Rules-Data-Mining-Books. Apriori Algorithm, Association rules with 10% Support and 70% confidence, Association rules with 20% Support and 60% confidence, Association rules with 5% Suppo…
Output variable -> y y -> Whether the client has subscribed a term deposit or not Binomial ("yes" or "no") Attribute information For bank dataset Input variables: # bank client data: 1 - age (numer…
Use decision trees to prepare a model on fraud data treating those who have taxable_income <= 30000 as "Risky" and others are "Good" Data Description : Undergrad : person is under graduated or not …
Random Forest Assignment About the data: Let’s consider a Company dataset with around 10 variables and 400 records. The attributes are as follows: Sales -- Unit sales (in thousands) at each locat…
Use Random Forest to prepare a model on fraud data treating those who have taxable_income <= 30000 as "Risky" and others are "Good"
Implement a KNN model to classify the animals in to categorie
Prepare a model for glass classification using KNN Data Description: RI : refractive index Na: Sodium (unit measurement: weight percent in corresponding oxide, as are attributes 4-10) Mg: Magnesium…
classify the Size_Categorie using SVM
Prepare a classification model using SVM for salary data
Look at the data given below. Plot the data, find the outliers and find out μ,σ,σ^
Prepare a classification model using Naive Bayes for salary data
For Text Mining assignment ONE: 1) Perform sentimental analysis on the Elon-musk tweets (Exlon-musk.csv) TWO: 1) Extract reviews of any product from ecommerce website like amazon 2) Perform emotion…
Forecast Airlines Passengers data set. Prepare a document for each model explaining how many dummy variables you have created and RMSE value for each model. Finally which model you will use for For…
Forecast the CocaCola prices data set. Prepare a document for each model explaining how many dummy variables you have created and RMSE value for each model. Finally which model you will use for For…
PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS
The dataset contains 36733 instances of 11 sensor measures aggregated over one hour (by means of average or sum) from a gas turbine. The Dataset includes gas turbine parameters (such as Turbine Inl…
Assignment About the data: Let’s consider a Company dataset with around 10 variables and 400 records. The attributes are as follows: Sales -- Unit sales (in thousands) at each location Competitor P…