Stock-Prediction-Using-Twitter-Sentiment-Analysis

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.

A python library for decision tree visualization and model interpretation.

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.).

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

Composable data visualisation library for web with a data-first approach now powered by WebAssembly

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

The most complete library for Bar, Line, Area, Pie, Donut, Stacked Bar, Population Pyramid and Radar charts in React Native. Allows 2D, 3D, gradient, animations and live data updates.

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

Machine Learning inference engine for Microcontrollers and Embedded devices

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