Insights
Stay ahead of trends and techniques in data analytics and AI-ML from our densely certified team of engineering leaders, including 4 AWS Ambassadors along with experts on every cloud and data platform.
Deploying the Churn Prediction Model in Production
Overview
Deploying a churn prediction model into production is the final step in leveraging machine learning insights to drive business...
Read moreBenefits and Limitations of BigQuery ML for Churn Prediction
Overview
This project demonstrated how BigQuery ML can be used to predict customer churn efficiently and at scale. By leveraging...
Read moreEvaluating Model Performance: Metrics and Insights
Overview
Model evaluation is the next step in any machine learning pipeline. It helps us determine how well our models perform and whether they...
Read moreHyperparameter Tuning and Model Optimization
Overview
Hyperparameter tuning is a critical step in machine learning, as it fine-tunes the model to achieve optimal performance. By adjusting...
Read moreBuilding the Churn Prediction Model with BigQuery ML
Overview
Predicting customer churn is important in every industry, as it helps companies proactively retain customers at risk of leaving. For...
Read moreLoading and Preparing Customer Data for BigQuery ML
Overview
Data preparation is a foundational step in any machine learning project, impacting both model performance and interpretability. Properly...
Read moreVisualizing Churn Predictions in AWS QuickSight: Building Dashboards for Business Insights
AWS QuickSight provides an intuitive platform for visualizing churn prediction results generated by SageMaker Canvas. By building custom dashboards,...
Read moreInfrastructure Setup with Terraform for BigQuery ML
Overview
This article covers the initial infrastructure setup for deploying a churn prediction model in Google Cloud Platform...
Read moreEnd-to-End Deployment of Azure Serverless Web App Using Terraform
Deploying a serverless web app with Azure requires a seamless integration of static and dynamic components. Using Terraform, we can automate the...
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