Tag: #dataanalytics

  • Trending YouTube Video Data Science, NLP Predictions & Sentiment Analysis

    Trending YouTube Video Data Science, NLP Predictions & Sentiment Analysis

    Table of Contents Global YT WordCloud Let’s begin with the Kaggle YT TextHero dataset containing 3599 rows and 4 columns. Let’s set the working directory YOURPATH import osos.chdir(‘YOURPATH’) os. getcwd() and import all necessary modulesfrom wordcloud import WordCloud, STOPWORDSimport matplotlib.pyplot as pltimport pandas as pd Let’s read the input dataset df = pd.read_csv(r”youtube0.csv”, encoding =”latin-1″)…

  • SARIMAX Forecasting of Online Food Delivery Sales

    SARIMAX Forecasting of Online Food Delivery Sales

    This article provides a beginner-friendly guide to understanding and evaluating ARIMA-based time-series forecasting models such as SARIMA and SARIMAX. It focuses on an QC-optimized SARIMA(X) model to forecast the e-commerce sales of a food delivery company. The post covers essential concepts, data processing, model comparisons, and insights. It also includes a comparison between SARIMA and…

  • Cloud-Native Tech Status Update Q3 2022

    Cloud-Native Tech Status Update Q3 2022

    Cloud Computing Trends Q3 2022, market Share update key services IaaS PaaS FaaS Saas Cloud digital transformation all-the-way DevSecOps CI/Cd GitLab MLOps IoT Tech GCP gateway Big data Deloitte use-cases Stock markets Health Tech Cybersecurity Highlights Events Webinars AWS Storage E-training

  • Simple E-Commerce Sales BI Analytics

    Simple E-Commerce Sales BI Analytics

    Good businesses learn from previous efforts and test future ideas using e-commerce analytics (ECA). ECA enable you to delve deep into historical BI data, and future forecasting so that you can make the optimized business decisions.  The key benefits of ECA are as follows: Let’s look at the warehouse optimization problem by analyzing Kaggle sales…

  • K-means Cluster Cohort E-Commerce

    K-means Cluster Cohort E-Commerce

    K-means Clusters – Cohort Analysis applied to E-Commerce Understanding who your customers are and what they want is a fundamental part of any successful business. It can become increasingly challenging to create a one-size-fits-all customer profile. This is where the concept of cluster-based cohort analysis comes in. 

  • Customer Churn/Retention Rate ML/AI Strategies that Work!

    Customer Churn/Retention Rate ML/AI Strategies that Work!

    Telco Customer Churn/Retention Rate ML/AI Strategies that Work! Machine learning could predict customers with high probability to churn! Cohort analysis is a way to understand customer churn (aka attrition). In doing so, we maximize the ratio max [ (Customer Retention Rate)/(Customer Churn Rate) ]