2022 Coursera Machine Learning Specialization Optional Labs and Programming Assignments
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Updated
Mar 27, 2023 - Jupyter Notebook
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"
Cost-Aware Robust Tree Ensembles for Security Applications (Usenix Security'21) https://arxiv.org/pdf/1912.01149.pdf
Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference
Efficient Decision tree Ensembles libary for IoT edge nodes
Distributed decision-making system with Jade and Weka
adaXT: tree-based machine learning in Python
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
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
This repository contains my coursework and projects completed during the Machine Learning Specialization offered by DeepLearning.AI and Stanford Online.
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