TpotA Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
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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.
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RoffildlibraryLibrary for MQL5 (MetaTrader) with Python, Java, Apache Spark, AWS
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SharplearningMachine learning for C# .Net
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Machine Learning With PythonPractice and tutorial-style notebooks covering wide variety of machine learning techniques
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Jsmlt🏭 JavaScript Machine Learning Toolkit
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SporfThis is the implementation of Sparse Projection Oblique Randomer Forest
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DtreevizA python library for decision tree visualization and model interpretation.
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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
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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
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QuickmlA fast and easy to use decision tree learner in java
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Mljar SupervisedAutomated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀
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Machine Learning In RWorkshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
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Grtgesture recognition toolkit
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AIML-ProjectsProjects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
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Deep ForestAn Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
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Pytorch classification利用pytorch实现图像分类的一个完整的代码,训练,预测,TTA,模型融合,模型部署,cnn提取特征,svm或者随机森林等进行分类,模型蒸馏,一个完整的代码
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Tensorflow Ml Nlp텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)
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Isl PythonSolutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
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MachineLearningSeriesVídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.
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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!
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Orange3🍊 📊 💡 Orange: Interactive data analysis
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Edarfexploratory data analysis using random forests
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EmlearnMachine Learning inference engine for Microcontrollers and Embedded devices
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25daysinmachinelearningI will update this repository to learn Machine learning with python with statistics content and materials
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cqrConformalized Quantile Regression
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Cnn Svm ClassifierUsing Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
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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.).
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ShifuAn end-to-end machine learning and data mining framework on Hadoop
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Awesome Decision Tree PapersA collection of research papers on decision, classification and regression trees with implementations.
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ThundergbmThunderGBM: Fast GBDTs and Random Forests on GPUs
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GrfGeneralized Random Forests
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InfiniteboostInfiniteBoost: building infinite ensembles with gradient descent
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MachinelearnjsMachine Learning library for the web and Node.
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Ml ProjectsML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
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User Machine Learning TutorialuseR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html
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Rrcf🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
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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
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Decision Tree JsSmall JavaScript implementation of ID3 Decision tree
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RandomforestexplainerA set of tools to understand what is happening inside a Random Forest
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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)
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