#Ensemble-learning
Showing 45 of 45 repositories tagged #ensemble-learning, ranked by stars
Fast and Accurate ML in 3 Lines of Code
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
Merlion: A Machine Learning Framework for Time Series Intelligence
A collection of research papers on decision, classification and regression trees with implementations.
A Julia machine learning framework
General Assembly's 2015 Data Science course in Washington, DC
😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切：论文、代码、框架与库
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
ML-Ensemble – high performance ensemble learning
Python package for stacking (machine learning technique)
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
Official Codebase for "Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights" (ICML 2026 Spotlight)
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
[NeurIPS'25]🛠️Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库
End-to-end ensemble trading framework that trains, backtests, and promotes validated strategies to live execution.
useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
Ensemble learning related books, papers, videos, and toolboxes
[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架
Fully automatic brain tumour segmentation using Deep 3-D convolutional neural networks
Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
Dataflow Programming for Machine Learning in R
python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.
Determine whether a given video sequence has been manipulated or synthetically generated
Machine Learning Algorithms on NSL-KDD dataset
A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)
Using Deep Learning for Emotion Classification on EEG signals (SEED Dataset). CNN, RNN, Hybrid model, and Ensemble
Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification
For our ISSTA20 paper "CoCoNuT: Combining Context-Aware Neural Translation Models using Ensemble for Program Repair" by Thibaud Lutellier, Hung Viet Pham, Lawrence Pang, Yitong Li, Moshi Wei and Lin Tan
An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Source code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.
🤖 Python implementations of some of the fundamental Machine Learning models and algorithms from scratch with interactive Jupyter demos and math being explained.
Some example projects that was made using Tensorflow (mostly). This repository contains the projects that I've experimented-tried when I was new in Deep Learning.
EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification
MABEL: Malware Analysis Benchmark for Artificial Intelligence and Machine Learning
Here my amazing tutorial collection contain amazing notebook must read. It's contain pytorch, Advance pandas, Ensemble learning, Tensorflow, Genetic Algorithms, Dask, Word Embedding
Natural Language Processing for Multiclass Classification: A repository containing NLP techniques for multiclass classification of text data.
A Deep Learning ensemble that classifies Windows executable files as either benign, ransomware, or other malware.
Moody's Bond Rating Classifier and USPHCI Economic Activity Forecast Modeling
An advanced, production-ready quantitative trading system built on top of Microsoft Qlib
Cross-platform mobile application with multiple features targeting agricultural community
Advanced ML system for stock market prediction with real-time data and multiple algorithms