Ramgopal Prajapat:

Learnings and Views

Insurance Agent Attendance System using Deep Learning Ram - Sep 25, 2021
Employed Insurance agents visit their prospective leads for educating on insurance policies and selling the right policies. For the banks and insurance agencies, it is important that their agents visit customers and build trust & long-term relationships. Tracking visits of the agents to their client locations is important for planning …
Data Scientist Interview Questions - Financial Services Ram - Jul 21, 2021
In this blog, we list a series of questions typically asked during interview process for Sr Data Scientist role in Financial Services.
Wonderful Word Cloud in Python Ram - Jun 19, 2021
Word Cloud is one of the visualization techniques to show relative importance of key words. Based on frequency of occurrences, it finds the importance for each word. From the large corpus of textual information, we want find the key words and topics, the word cloud can be really good starting …
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 …