an open-sourced highly automated machine learning Python framework for data-driven geochemistry discovery
-
Updated
Jun 7, 2025 - Python
#
flaml
Here are 15 public repositories matching this topic...
Using machine learning to predict Goodreads ratings utilizing the Kedro framework. Includes EDA, rich feature engineering and data integration, model building with pipelines, and model comparison
-
Updated
Mar 3, 2025 - Jupyter Notebook
Build your own Recommendation Systems !!!
python data-science machine-learning pandas artificial-intelligence recommendation-system automl ranking-algorithm regression-algorithms h2o-automl optuna mljar-supervised flaml
-
Updated
Apr 21, 2022 - Jupyter Notebook
AutoML Libraries for training multiple ML models in one go with less code.
tpot auto-sklearn mljar h2o-automl transmogrifai auto-viml autogluon pycaret evalml hyperopt-sklearn auto-keras lightautoml flaml
-
Updated
Jul 12, 2022 - Python
Binary Classification problem. Contains Classifiers from various AutoML libraries such as AutoGluon, FLAML, Lazypredict, & TPOT
machine-learning prediction classification binary-classification automl tpot automated-machine-learning autogluon lazypredict tpot-classifier flaml
-
Updated
Dec 26, 2024 - Jupyter Notebook
Using FLAML to build a ML model for predicting University Admission chances
-
Updated
Oct 4, 2024 - Jupyter Notebook
Here, I will put Machine learning tasks which are done using Automated Machine Learning.
-
Updated
Dec 24, 2023 - Jupyter Notebook
This repository is associated with interpretable/explainable ML model for liquefaction potential assessment of gravelly soils. This model is developed using LightGBM and SHAP.
machine-learning lightgbm artficial-intelligence earthquake automl geotechnical-engineering explainable-artificial-intelligence earthquake-engineering liquefaction shap shear-waves gravel explainable-machine-learning shapley-additive-explanations lightgbm-classifier geotechnics flaml
-
Updated
Mar 28, 2024 - Jupyter Notebook
Best practices for solving Machine Learning Classification problems with advanced tools
python machine-learning sklearn xgboost classification lightgbm gradient-boosting-classifier catboost optuna flaml
-
Updated
Apr 4, 2023 - Jupyter Notebook
Autism Prediction in Adults
data-science machine-learning artificial-intelligence classification-algorithm autism-spectrum-disorder xgboost-algorithm optuna catboost-model lightgbm-models automl-algorithms flaml
-
Updated
Jun 15, 2022 - Jupyter Notebook
ACAML is an Adaptive Constraint-Aware AutoML web app built with Streamlit. It automatically selects the best model for regression or classification tasks using FLAML, displays performance metrics, and provides SHAP-based feature explanations. Empower users to run and interpret ML models easily.
python machine-learning machine-learning-algorithms regression data-visualization classification data-analysis hyperparameter-tuning automl machine-learning-models feature-importance end-to-end-machine-learning applied-machine-learning shap model-interpretability ml-application flaml time-budget-ml user-friendly-ml
-
Updated
May 31, 2025 - Python
-
Updated
Oct 6, 2021 - Jupyter Notebook
2023 Columbia ADI Hackathon: Best Beginner Prize
-
Updated
Mar 21, 2023 - Python
Improve this page
Add a description, image, and links to the flaml topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the flaml topic, visit your repo's landing page and select "manage topics."