Types of machine learning algorithm
What is machine learning? Machine Learning refers to the techniques involved in dealing with vast data in the most intelligent fashion (by developing algorithms) to derive actionable insights. Machine learning…
Day: February 3, 2022
Data Science
Basics of statistics for data science: Type of data measurement scale
Basics of statistics for data science: Type of data measurement scale Before understanding the type of data, let us try to understand the properties of measurement. These measurement properties are identity,…
Data Science
Basics of Statistics for Data Science: How to calculate Z score
Z score is a statistic used to measure the number of standard deviations above or below the mean of your population. Therefore to calculate your Z score, you will need…
Data Science
Read and import different data files in R: Excel, CSV, SPSS, txt, url
Steps to Read and import different data files in R Using point and click option without R codes 1. Click on file (Top left corner) 2. Click on Import datasets…
Data Science
Predictive model for Bank customer churn using machine learning
This case study study is about predicting customer churn in Banks. Please download the dataset given below. DATASET This dataset contains following variables. RowNumber CustomerId Surname CreditScore Geography Gender Age…
Data Science
Datasets for practicing data science and machine learning
1. Titanic dataset 2. Targeted Marketing Campaign 3. Bank customer Churn 4. Credit Risk: Predicting loan default 5. Cluster analysis for RFM
Data Science
Credit Risk: Predictive machine model for loan default with R codes
This case study discusses steps to build loan default model using machine learning with R codes. Download the dataset Download the dataset by clicking on dataset no 4. entitled “Credit…
Data Science
Introduction to Basics of R: Getting Started in R and RStudio
Start your Base R on your laptop or computer Basically, R and Rstudio are the same software, however RStudio is an Integrated Development Environment (IDE) wherein you can run, edit…
Data Science
How to Create, Modify, and access elements of Create, Modify, access elements of Vectors in Rstudio
# Let us create vectors in R# Vectors are one-dimension arrays that can hold numeric data, character data, or logical data. # vector defination in R # numeric vectorage <-…
Data Science
Data Visualization with R codes: Barplots and Scatter plots
Read the earlier article to understand the data by clicking on the link below https://lightgray-cattle-549464.hostingersite.com/post/data-visualization-with-r-histogram-boxplot-piechart-mosiacplot-correlation Barplot barplot(table(dataset$age)) # dataput to the command must be vector or matrix# If you…
Data Science
Data visualization with R: Histogram, Boxplot, Piechart, Mosiacplot, Correlation
Download the dataset by clicking on the below link Targeted Marketing Campaign data Alternatively this dataset is also available at We rename the data as dataset in R # Assigning…
Data Science
Metrics to evaluate classification models with R codes: Confusion Matrix, Sensitivity, Specificity, Cohen’s Kappa Value, Mcnemar’s Test
This article aims to discuss various evaluation / performance metrics of machine learning based classification models. There are atleast a minimum of 15 different metrics for evaluating the model. These…
CRM
Logistic regression with R codes
Train the model using the training sets and check score logistic <- glm(formula = Survived ~ Pclass + Sex + Embarked + Age, data = train, family ="binomial") summary(logistic) #…
Data Science
Decision trees with R codes
Decision tree can be used for both classification and regression problems. Terminologies Related To Decision Tree •Root Node Splitting Decision Node Leaf/Terminal Node Pruning Branch/ Sub Tree Parent/Child Node •Algorithms used…
Data Science
Factors in RStudio: Analysing categorical data
## Factors in R> > theory <- "R uses factors for categorical variables!"> > # factor refers to a statistical data type used to store categorical variables.> # Example gender>…
Data Science
Create data frame from Vectors in RStudio
> ### Dataframes are two dimensional structure with rows and columns. Basically, it is an array of vectors of equal length.> It is similar to a tabular data with the…
CRM
Targeted Marketing Campaign for cross-sell of Term Deposits: Predicting conversion of cross-selling using machine learning
# Setting up working directorysetwd("")# Getting working directorygetwd()# Import the data install.packages("readr")library(readr)raw_dataset <- read_csv("C:/Users/91917/Desktop/raw_dataset.csv")View(raw_dataset)dataset <- raw_dataset## Data explorationstr(dataset)head(dataset)tail(dataset)View(dataset)dataset$job <- as.factor(dataset$job)dataset$marital <- as.factor(dataset$marital)dataset$age <- as.numeric(dataset$age)dataset$job <- as.factor(dataset$job)dataset$marital <- as.factor(dataset$marital)dataset$education <- as.factor(dataset$education)dataset$default…
Data Science
Predicting Telecom customer Churn: Machine learning in R
setwd("")library(readr)WA_Fn_UseC_Telco_Customer_Churn <- read_csv("WA_Fn-UseC_-Telco-Customer-Churn.csv")View(WA_Fn_UseC_Telco_Customer_Churn)dataset <- WA_Fn_UseC_Telco_Customer_Churnstr(dataset)head(dataset)tail(dataset)View(dataset)# Converting to factorsdataset$gender <- as.factor(dataset$gender)dataset$SeniorCitizen <- as.factor(dataset$SeniorCitizen)dataset$Partner <- as.factor(dataset$Partner)dataset$Dependents <- as.factor(dataset$Dependents)dataset$PhoneService <- as.factor(dataset$PhoneService)dataset$MultipleLines <- as.factor(dataset$MultipleLines)dataset$InternetService <- as.factor(dataset$InternetService)dataset$OnlineSecurity <- as.factor(dataset$OnlineSecurity)dataset$OnlineBackup <- as.factor(dataset$OnlineBackup)dataset$DeviceProtection <- as.factor(dataset$DeviceProtection)dataset$TechSupport <- as.factor(dataset$TechSupport)…
Data Science
Unsupervised machine learning Creating Segments using RFM data Kmeans clustering in R
#creating a fresh copy of the data to work on so that the imported original data is intact and can be reverted back easilyView(Deleted_negative_price_quantity)dataset <- Deleted_negative_price_quantityView(dataset)str(dataset)# 541909 obs. of 8…
Digital marketing
Content format for consumer engagement and digital marketing
The following are the dominant content format being used for boosting consumer engagement. This content could be in the form of either Text, image or video or a combination of…
Digital marketing
Automated bidding strategy and campaign goals
There are basically 4 types of bid strategy 1. Visibility 2. Clicks 3. Conversions (Value or unit) 4. View or interactions (for Video ads)
Digital marketing
What is Technical SEO?
The objective of the technical SEO is to ensure that Google search engine is able to crawl and index your website appropriately. Search engine prefers a certain structure to the…
Data Science
Data Science for beginners: Step by step approach to learn with R programming
This free course on data science for beginners will introduce you to the world of data science and machine learning. You will learn what is data science? You will also…