2022 Coursera Machine Learning Specialization Optional Labs and Programming Assignments

(ICLR 2024) GRANDE: Gradient-Based Decision Tree Ensembles

Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.

[NeurIPS 2020] Code for "An Efficient Adversarial Attack for Tree Ensembles"

Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference

Cost-Aware Robust Tree Ensembles for Security Applications (Usenix Security'21) https://arxiv.org/pdf/1912.01149.pdf

Efficient Decision tree Ensembles libary for IoT edge nodes

adaXT: tree-based machine learning in Python

Distributed decision-making system with Jade and Weka

TREe Ensemble COmpiler for efficient inferences

Contains solutions and notes for the Machine Learning Specialization by Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng

This repository contains my coursework and projects completed during the Machine Learning Specialization offered by DeepLearning.AI and Stanford Online.

Protree is a project examining using prototypes in explaining ensembles of tree classifiers

Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng

Comparison of tree ensemble machine learning methods in predicting revenue outcome for an e-commerce site