Amazon Transcribe Live Call Analytics (LCA) Sample Solution
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Updated
Oct 25, 2024 - JavaScript
Amazon Transcribe Live Call Analytics (LCA) Sample Solution
Comprehensive Power BI dashboards showcasing insights on Call Centre Trends, Customer Retention, and Diversity & Inclusion to drive business impact.
Official Repo for python-vcon and py-vcon-server Python packages
Predict which customers should a call-center call for greater assertiveness in a sale
Agent Insights & Call Activity at Your Fingertips. This Power BI dashboard tracks calls answered, answer speed, & customer satisfaction. Built with Power BI & Excel.
ARCH and GARCH models along with MLOps pipeline using AWS platform to deploy model in a production environment.
An AWS serverless AI services pipeline for analysing call center calls, with custom analytics built around AWS Transcribe and AWS Comprehend and insights published on AWS Quicksight.
VB.Net code for interfacing with Avaya's CMS Supervisor call center management software.
This shows my complete Power BI dashboards with real world data provided by PWC Switzerland. This is a Forage virtual internship where I got to use, analyze and gain valuable insights using real world data
Power BI Dashboards and Power Point Presentations
This analysis measures the performance of a call centre and assessed the satisfactions and sentiments of customers.
Time series model using multiple linear regression on call-centre data.
Comprehensive Power BI dashboards showcasing insights on Call Centre Trends, Customer Retention, and Diversity & Inclusion to drive business impact.
PwC Switzerland Power BI in Data Analytics Virtual Case Experience helps build foundation in data analysis and visualization with Power Bi
Gaussian Time Series model and MLOps pipeline using the AWS to deploy the model in a production environment.
an internship where i use different data set and analyse call centre trend , churn analysis and diversity inclusion analysis
Excel-based analysis of call center performance metrics, focusing on operational efficiency and customer satisfaction.
This project involves helping a telecoms company better understand how its call center operations are performing on a daily basis.
Call center statistical analytics for staffing level.
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