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VishalKumar-S / Sales_Conversion_Optimization_MLOps_Project

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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.

python docker data-science machine-learning continuous-integration data-validation predictive-modeling model-evaluation interpretability mlops h2o-automl shap github-actions streamlit data-drift neptune-ai zenml email-alerts sales-optimization evidently-ai
  • Updated Mar 1, 2024
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shaheennabi / US-visa-machine-learning-end-to-end-project

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🎇 End-to-End ML Pipeline: US_VISA 🎆 An end-to-end machine learning pipeline built for the US_VISA project 🔄, including data ingestion, validation, training, and prediction. 🧠💼 Using MongoDB for storage, EvidentlyAI for drift detection, and AWS for deployment, all automated with GitHub Actions 🚀. Dockerized and ready to scale! 🔥

docker aws-s3 aws-ecr aws-ec2 cicd github-actions evidently-ai
  • Updated Nov 15, 2024
  • Jupyter Notebook

VivekShinde7 / US-Visa-Approval-Prediction

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This project helps streamline the visa approval process by using machine learning to predict the likelihood of US visa approval for employees. It can assist immigration officials in making quicker, data-driven decisions, reduce manual work, and enhance accuracy.

python git docker aws machine-learning mongodb scikit-learn jupyter-notebook s3-storage cicd ecr-registry gitactions-workflow evidently-ai us-visa-prediction
  • Updated Oct 3, 2024
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