An Advanced Web Application Firewall that protects against threats like SQL injection and XSS by filtering HTTP traffic. It combines signature-based detection and machine learning-based anomaly detection to identify obfuscated, zero-day, and unknown attacks through behavioral analysis.

Easy Custom Losses for Tree Boosters using Pytorch

No-Caffeine-No-Gain's Deep Knowledge Tracing (DKT)

Crypto & Stock* price prediction with regression models.

🌳MultiLGBM🌳: A simple multi-objective regression example to show how to trade-off objectives on the Pareto front with a single LGBM model.

A project that demonstrates the use of the lgbm C++ API to perform inference without any python dependencies.

A collection of LightGBM callbacks. (DART early stopping, tqdm progress bar)

integrated neural network library

🌬️ Wind Speed Prediction Model using Machine Learning. ⚡ LightGBM for fast, reliable results. 📊 Visualize feature importance & performance. 💻 Interactive Streamlit Web UI & 🖥️ Desktop GUI. 🔬 Perfect for research & analysis of wind speed.

LGBM and logistic regression for prediction of customers' second time transaction for an online market app.

Music Genre Recommender website that can identify and recommend 10 different genres of music using Light Gradient Boosting Machine (LGBM). An accuracy of 90% was achieved on the test set by tuning the hyperparameters of the model with Optuna.

Find LGBM Hyperparams and train the model

🏠 Predict house prices accurately using machine learning with Python and Flask in this complete end-to-end project.

Telecom churn prediction using ML models with interactive Streamlit app

Microsoft Malware Prediction Challenge. 8th position solution.

Repository for the "Google Analytics Customer Revenue Prediction" Kaggle competition.

In this project I used basic classification algorithms including random forest, xgboost and decision tree to reach the best solution, finding out how many survived in the titanic accident. I use Kaggles free GPUs and Datasets in this project. I used different feature engineering techniques to clean my data

Predict the quality of wikipedia articles using AI

Script to compile LightGBM models to optimized shared libraries (.so, .dylib, or .o files) using lleaves.