deep learning and scientific computing framework with native CPU and GPU backend for the Scala programming language
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Updated
Apr 22, 2025 - Scala
deep learning and scientific computing framework with native CPU and GPU backend for the Scala programming language
sklearn, tensorflow, random-forest, adaboost, decision-tress, polynomial-regression, g-boost, knn, extratrees, svr, ridge, bayesian-ridge
the aim of this project is to develop a machine learning model to predict temperature and rainfall based on environmental features, with a specific focus on six air quality parameters identified by the World Health Organization (WHO).
A project on predicting snow depth using L-Band InSAR parameters.
Real-time fraud detection system — ExtraTrees, F1=0.8962 on 284K transactions, FastAPI + Streamlit, SHAP explainability
PHRC-TAGS: voltage-only cross-capacity external-short-circuit detection for LiFePO4 cells, with frozen models, audits, and publication figures.
Predict product failures
Data Science and Machine Learning using Python and R
DACON/ETRI ICTC code package for personalized digital bedtime routine modeling with ExtraTrees shrinkage
End-to-end machine-learning project that predicts telecom customer-churn with 81.5 % accuracy: cleans data, benchmarks Random Forest / XGBoost / LightGBM, tunes ExtraTrees via RandomizedSearchCV, and ranks the features that matter most.
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