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h2oai / h2o-3

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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.

python java data-science machine-learning opensource r big-data spark deep-learning hadoop random-forest gpu naive-bayes h2o distributed pca gbm ensemble-learning automl h2o-automl
  • Updated Nov 19, 2024
  • Jupyter Notebook

EnnengYang / Awesome-Model-Merging-Methods-Theories-Applications

Star 216

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.

generative-model ensemble-learning transfer-learning zero-shot-learning robustness multi-task-learning attack-defense generalization meta-learning model-fusion federated-learning continual-learning few-shot-learning diffusion-models multi-domain-learning foundation-models large-language-models llms model-merging knowledge-fusion
  • Updated Nov 15, 2024

vignesh4005 / Crowdfunding_Campaign_Success_Prediction

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This project aims to predict the success of crowdfunding campaigns using machine learning models: Ensemble Learning, Naive Bayes, and Support Vector Machine (SVM).

statistics exploratory-data-analysis naive-bayes-classifier ensemble-learning boosting-algorithms support-vector-machines gradient-boosting-classifier random-forest-classifier xgboost-classifier adaboostclassifier bagging-classifier
  • Updated Nov 12, 2024
  • Jupyter Notebook

erenyeager101 / Heart-Disease-monitoring

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Patients can enter their symptoms and relevant health data (like heart rate, blood pressure, etc.) into the frontend interface. The model can analyze this data instantly and provide immediate feedback on their heart health status. After analyzing patient data, the system can offer personalized lifestyle recommendations.

github python flask machine-learning render ensemble-learning hybrid-machine-learning
  • Updated Nov 10, 2024
  • HTML

ketanip / productivity-loss-predictor

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ML based productivity loss by prediciton! This project explores how social media usage impacts productivity and provides a predictive model to assess productivity loss. It combines data exploration, preprocessing, model training, and an interactive web app interface for a smooth user experience.

jupyter-notebook python3 ensemble-learning data-preprocessing feature-engineering predictive-modeling data-exploration data-pipelines data-cleaning hyperparameter-tuning voting-classifier python-pickle productivity-loss-prediction social-media-usage-analysis impact-of-social-media-on-productivity machine-learning-model-training regression-and-classification-models streamlit-web-application user-interface-for-ml-model
  • Updated Nov 10, 2024
  • Jupyter Notebook

Koon-Kiat / Spam-And-Phishing-Detection-Using-Machine-Learning

Star 3

This project leverages advanced machine learning algorithms to detect and classify malicious emails, focusing on spam and phishing threats. As email threats grow more sophisticated, accurate detection is critical to ensuring the security and privacy of both individuals and organizations.

nlp flask machine-learning pipeline cross-validation pytorch transformer nltk ensemble-learning spam-detection bert l1l2-regularization outlook-addin noise-injection pythonanywhere stacked-ensembles phishing-detection optuna
  • Updated Nov 6, 2024
  • Python

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