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Statistical Tests using Python Ram - Apr 04, 2021

In this blog, we will discuss T-Test (two-sample), ANOVA, Chi-Square, and Correlation Analysis in Python

Customer Attrition Model using Decision Tree Ram - Apr 03, 2021

It is costly to acquire a new customer, hence banks and other organizations work to keep their customer engaged (or reduce the customer attrition) Customer Attrition can be silent (when a customer stops using a product) and explicit when a customer closes a product. Typically, there is a journey or …

Bivariate Analysis: Contingency Analysis and Chi Square Ram - Apr 02, 2021

For finding an association between two nominal variables, a contingency analysis table, and chi-square test is employed. The contingency table is created by listing the values of one variable as a row and the other as a column. The Pearson chi-square test or "goodness-of-fit” is used to check if the …

Retail Analytics - eCommerce Data EDA and Simple Segmentation ram_admin - Feb 26, 2021

In this blog, we will learn about Exploratory Data Analysis (EDA) on eCommerce Data and also develop a simple segmentation. Based on order count, amount and recency are used to create the features and then created rule-based segmentations. In the subsequent blogs, we may use the same data for machine …

Setting up MYSQL instance on GCP and Learning SQL Ram - Jan 28, 2021

In this blog, we will set up MYSQL instance on Google Cloud (GCP) and connect MySQL Workbench to GCP MYSQL Instance. In the part two, we will design a simple database schema for a retail scenario and create the list of tables. Also, we will load CSV files to the …

SQL Scenarios for Practice and Learning Ram - Jan 28, 2021

In the previous blog, we have covered MYSQL database design for retail scenario, create table structure and import CSV data into these tables. Also, we have covered 10 SQL scenario to learn the basics of SQL programming for Data Analytics. In continuation of that, we are adding 11 more scenarios …

K Means Clustering Examples and Practical Applications Ram - Jan 07, 2021

In this blog, a list of real life scenarios of K Means Clustering Applications are discussed. There are list of real world examples and with a list of features to be used for K Means clustering.

Decision Tree: A statistical and analytical tool for effective decisions Ram - Dec 28, 2020

A decision tree is a hierarchical or tree-like representation of decisions. A Decision Tree is a technique to iteratively break input data (or node) into two or more data samples (or nodes). And this recursive partitioning of input data (or node) continues until it meets specified condition(s). A Decision Tree …

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