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207 search results found

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

H2o 3 ⭐ 6,618

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.

Orange3 ⭐ 4,469

🍊 📊 💡 Orange: Interactive data analysis

Flaml ⭐ 3,500

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Machine Learning With Python ⭐ 2,980

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Mljar Supervised ⭐ 2,867

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Dtreeviz ⭐ 2,720

A python library for decision tree visualization and model interpretation.

Awesome Decision Tree Papers ⭐ 2,266

A collection of research papers on decision, classification and regression trees with implementations.

Benchm Ml ⭐ 1,839

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Gcforest ⭐ 1,242

This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'

Hyperparameter Optimization Of Machine Learning Algorithms ⭐ 1,025

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Awesome Gradient Boosting Papers ⭐ 930

A curated list of gradient boosting research papers with implementations.

Generalized Random Forests

Deep Forest ⭐ 823

An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)

gesture recognition toolkit

Thundergbm ⭐ 674

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Ai_all_resources ⭐ 647

A curated list of Best Artificial Intelligence Resources

Decision Forests ⭐ 635

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

Machinelearnjs ⭐ 532

Machine Learning library for the web and Node.

Fasttreeshap ⭐ 485

Fast SHAP value computation for interpreting tree-based models

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Chefboost ⭐ 428

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

Yggdrasil Decision Forests ⭐ 403

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

User Machine Learning Tutorial ⭐ 386

useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html

Sharplearning ⭐ 372

Machine learning for C# .Net

Emlearn ⭐ 327

Machine Learning inference engine for Microcontrollers and Embedded devices

Decisiontree.jl ⭐ 326

Julia implementation of Decision Tree (CART) and Random Forest algorithms

2018 Machinelearning Lectures Esa ⭐ 324

Machine Learning Lectures at the European Space Agency (ESA) in 2018

Handson Ml ⭐ 277

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Linear Tree ⭐ 253

A python library to build Model Trees with Linear Models at the leaves.

Intrusion Detection System Using Machine Learning ⭐ 248

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

The Python Workshop ⭐ 245

A New, Interactive Approach to Learning Python

Ml Projects ⭐ 243

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

Decision Tree Js ⭐ 237

Small JavaScript implementation of ID3 Decision tree

An end-to-end machine learning and data mining framework on Hadoop

Shapley ⭐ 198

The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).

P2Rank: Protein-ligand binding site prediction tool based on machine learning. Stand-alone command line program / Java library for predicting ligand binding pockets from protein structure.

Infiniteboost ⭐ 177

InfiniteBoost: building infinite ensembles with gradient descent

Aws Machine Learning University Dte ⭐ 177

Machine Learning University: Decision Trees and Ensemble Methods

Machine_learning_algorithms_from_scratch ⭐ 164

This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.

Handwritten Digit Recognition Using Deep Learning ⭐ 158

Handwritten Digit Recognition using Machine Learning and Deep Learning

The Data Science Workshop ⭐ 156

A New, Interactive Approach to Learning Data Science

Machine Learning In R ⭐ 144

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

Youtube Like Predictor ⭐ 126

YouTube Like Count Predictions using Machine Learning

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Compendium Of Free Ml Reading Resources ⭐ 106

Compendium of free ML reading resources

How To Score 0.8134 In Titanic Kaggle Challenge ⭐ 105

Solution of the Titanic Kaggle competition

Network Intrusion Detection ⭐ 85

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

Betaml.jl ⭐ 83

Beta Machine Learning Toolkit

Quantile Forest ⭐ 70

Quantile Regression Forests compatible with scikit-learn.

Ruby Scoring API for PMML

Covid19 Literature Clustering ⭐ 63

An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.

exploratory data analysis using random forests

Top 10 Machine Learning Methods With R ⭐ 61

Includes top ten must know machine learning methods with R.

Click Through Rate Prediction ⭐ 60

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

Predicting_real_estate_prices_using_scikit Learn ⭐ 59

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)

Nowtrade ⭐ 57

Python library for backtesting technical/mechanical strategies in the stock and currency markets

Droiddetective ⭐ 56

A machine learning malware analysis framework for Android apps.

Cl Random Forest ⭐ 55

Random forest in Common Lisp

Missranger ⭐ 53

R package "missRanger" for fast imputation of missing values by random forests.

Scikit Tree ⭐ 51

Scikit-learn compatible decision trees beyond those offered in scikit-learn

Isl Python ⭐ 50

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

Random Survival Forest ⭐ 50

A Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.

Heart_disease_prediction ⭐ 49

Heart Disease prediction using 5 algorithms

Fastrank ⭐ 48

My most frequently used learning-to-rank algorithms ported to rust for efficiency. Try it: "pip install fastrank".

25daysinmachinelearning ⭐ 48

I will update this repository to learn Machine learning with python with statistics content and materials

Go Scoring API for PMML

Aiml Projects ⭐ 44

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

Phishing Detection Plugin ⭐ 42

A lite chrome extension for detecting phishing sites using random forest classifier

Miceranger ⭐ 42

miceRanger: Fast Imputation with Random Forests in R

Oasw Concept Drift Detection And Adaptation ⭐ 42

An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams" published in IEEE Internet of Things Magazine.

Nsforest ⭐ 40

A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing

Icc 2019 Wc Prediction ⭐ 39

Predicting the winner of 2019 cricket world cup using random forest algorithm

Stock Market Sentiment Analysis ⭐ 38

Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe th

Malware_detect2 ⭐ 38

Malware Classification using Machine learning

Random Forest Mc ⭐ 38

Random Forest with Dynamic Tree Selection Monte Carlo Based (RF-TSMC).

Skranger ⭐ 37

scikit-learn compatible Python bindings for ranger C++ random forest library

Ml_segmentation ⭐ 29

Machine learning semantic segmentation - Random Forest, SVM, GBC

Broomstick ⭐ 29

🌲 broom helpers for decision tree methods (rpart, randomForest, and more!) 🌲

Rforestry ⭐ 29

Machinelearningseries ⭐ 28

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

Decision Trees For Ml ⭐ 27

Building Decision Trees From Scratch In Python

Arboreto ⭐ 27

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

Urb Studies Predicting Gentrification ⭐ 27

This repo is intended to support replication and exploration of the analysis undertaken for our Urban Studies article "Understanding urban gentrification through Machine Learning: Predicting neighbourhood change in London".

Machinelearning_breastcancer_python ⭐ 26

Machine Learning Applications using Sklearn, matplotlib, pandas, and seaborn

Landsat Time Series Analysis For Multi Temporal Land Cover Classification ⭐ 26

LANDSAT Time Series Analysis for Multi-temporal Land Cover Classification using Machine Learning techniques in Python and GUI development for automation of the process.

Machine Learning Models ⭐ 26

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

Github Stars Predictor ⭐ 25

It's a github repo star predictor that tries to predict the stars of any github repository having greater than 100 stars.

Nsl Kdd Network Intrusion Detection ⭐ 25

Machine Learning Algorithms on NSL-KDD dataset

Machine Learning library written in Python and NumPy.

Te2rules ⭐ 25

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

Trajectory Analysis And Classification In Python Pandas And Scikit Learn ⭐ 25

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently trajectories.

R Stats Machine Learning ⭐ 25

Misc Statistics and Machine Learning codes in R

Us Transportationmode ⭐ 24

Transportation Mode Detection with Unconstrained Smartphones Sensors

Causaltoolbox ⭐ 23

Ml Spam Sms Classification ⭐ 23

Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification

Disentangled Attribution Curves ⭐ 23

Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

Flexible Bayesian Optimization in R

Foresterror ⭐ 22

A Unified Framework for Random Forest Prediction Error Estimation

Shapley_regressions ⭐ 22

Statistical inference on machine learning or general non-parametric models

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