{"repo":"VishalKumar-S/Sales_Conversion_Optimization_MLOps_Project","free":true,"listed":false,"github":"https://github.com/VishalKumar-S/Sales_Conversion_Optimization_MLOps_Project","clone":"git clone https://github.com/VishalKumar-S/Sales_Conversion_Optimization_MLOps_Project.git","description":"Sales Conversion Optimization MLOps: Boost revenue with AI-powered insights. Features H2O AutoML, ZenML pipelines, Neptune.ai tracking, data validation, drift analysis, CI/CD, Streamlit app, Docker, and GitHub Actions. Includes e-mail alerts, Discord/Slack integration, and SHAP interpretability. Streamline ML workflow and enhance sales performance.","language":"HTML","stars":21,"topics":["continuous-integration","data-drift","data-science","data-validation","docker","email-alerts","github-actions","h2o-automl","interpretability","machine-learning"],"license":null,"category":"deployment-docker-iac","readme_excerpt":"Sales Conversion Optimization Project 📈 Deployed Application: Sales Conversion Optimisation Web App Table of Contents 📑 1. Project Description 📝 2. Project Structure 🏗️ 3. Necessary Installations 🛠️ 4. Train Pipeline 🚂 5. Continuous Integration Pipeline 🔁 6. Alert Reports 📧 7. Prediction App 🎯 8. Neptune.ai Dashboard 🌊 9. Docker Configuration 🐳 10. GitHub Actions and CML Reports 🛠️ 11. Running the Project 🚀 Project Description 🚀 Welcome to the Sales Conversion Optimization Project! 📈 This project focuses on enhancing sales conversion rates through careful data handling and efficient model training. The goal is to optimize conversions using a structured pipeline and predictive modeling. I've structured this project to streamline the process from data ingestion and cleaning to model training and evaluation. With an aim to empower efficient decision-making, my pipelines include quality validation tests, drift analysis, and rigorous model performance evaluations. This project aims to streamline your sales conversion process, providing insights and predictions to drive impactful business decisions! 📊✨ Live Demo Walkthrough : Project Structure 🏗️ Let's dive into the project structure! 📁 Here's a breakdown of the directory: - steps Folder 📂 - ingest data - clean data - train model - evaluation - production batch data - predict prod data - src Folder 📁 - clean data - train models - pipelines Folder 📂 - training pipeline - ci cd pipeline - models Folder 📁 - saved","default_branch":null,"files":null,"tree":[],"storefront":"/r/VishalKumar-S","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/VishalKumar-S/Sales_Conversion_Optimization_MLOps_Project/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}