Orange3🍊 📊 💡 Orange: Interactive data analysis
QuickmlA fast and easy to use decision tree learner in java
ShifuAn end-to-end machine learning and data mining framework on Hadoop
InfiniteboostInfiniteBoost: building infinite ensembles with gradient descent
ChefboostA Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python
Machine Learning Is All You Need🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!
Machine Learning ModelsDecision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
EmlearnMachine Learning inference engine for Microcontrollers and Embedded devices
Benchm MlA 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.).
Machine Learning In RWorkshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
Ml ProjectsML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
Isl PythonSolutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
Predicting real estate prices using scikit LearnPredicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
GcforestThis is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'
SporfThis is the implementation of Sparse Projection Oblique Randomer Forest
RoffildlibraryLibrary for MQL5 (MetaTrader) with Python, Java, Apache Spark, AWS
Edarfexploratory data analysis using random forests
Stock Market Sentiment AnalysisIdentification 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 the results of the model using Weka
25daysinmachinelearningI will update this repository to learn Machine learning with python with statistics content and materials
TpotA Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Cnn Svm ClassifierUsing Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
Mljar SupervisedAutomated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀
Jsmlt🏭 JavaScript Machine Learning Toolkit
Grtgesture recognition toolkit
H2o 3H2O 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.
ThundergbmThunderGBM: Fast GBDTs and Random Forests on GPUs
Deep ForestAn Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
GrfGeneralized Random Forests
Rrcf🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
DtreevizA python library for decision tree visualization and model interpretation.
MachineLearningSeriesVídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.
2020plusClassifies genes as an oncogene, tumor suppressor gene, or as a non-driver gene by using Random Forests
linear-treeA python library to build Model Trees with Linear Models at the leaves.
GeFsGenerative Forests in Python
EurekaTreesVisualizes the Random Forest debug string from the MLLib in Spark using D3.js