🍊 📊 💡 Orange: Interactive data analysis
A fast and easy to use decision tree learner in java
An end-to-end machine learning and data mining framework on Hadoop
InfiniteBoost: building infinite ensembles with gradient descent
A 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 Models
Decision 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
Machine Learning inference engine for Microcontrollers and Embedded devices
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.).
Machine Learning In R
Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
Predicting real estate prices using scikit Learn
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)
This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'
This is the implementation of Sparse Projection Oblique Randomer Forest
Library for MQL5 (MetaTrader) with Python, Java, Apache Spark, AWS
exploratory data analysis using random forests
Stock Market Sentiment Analysis
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 the results of the model using Weka
I will update this repository to learn Machine learning with python with statistics content and materials
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Cnn Svm Classifier
Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀
gesture recognition toolkit
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.
ThunderGBM: Fast GBDTs and Random Forests on GPUs
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
Generalized Random Forests
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
A python library for decision tree visualization and model interpretation.
Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.
Classifies genes as an oncogene, tumor suppressor gene, or as a non-driver gene by using Random Forests
A python library to build Model Trees with Linear Models at the leaves.
Generative Forests in Python
Visualizes the Random Forest debug string from the MLLib in Spark using D3.js