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h2o-automl

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H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

  • Updated Dec 15, 2024
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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.

  • Updated Mar 1, 2024
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In this project, we will identify the characteristics of women who are more likely to develop cervical cancer and use Automatic Machine Learning H2O AutoML to make prediction on whether or not a certain customer would buy a term deposit. We will also use Explainable AI (XAI) methods such as Variable Importance Plot, Partial Dependence Plot, SHAP…

  • Updated Oct 13, 2021
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My Final Submission for the 'Santander Customer Transaction Prediction'. I have participated in this very tough and interesting competition on Kaggle a while ago and I finally got the time to put all the work together in this Repo.

  • Updated Jul 10, 2019
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We will leverage population's information on immunization, mortality, social- economic and other health related factors and use Automatic Machine Learning H2O AutoML to make prediction on life expectancy of a certain population. We will also use Variable Importance Plot, Partial Dependence Plot, and SHAP Summary Plot to explain how each of our f…

  • Updated Oct 9, 2021
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