Popular GitHub Repositories for Black Forest Decor

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

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

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

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

A python library for decision tree visualization and model interpretation.

Deep learning software for colorizing black and white images with a few clicks.

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

基于图像识别的自动化黑盒测试框架 | An automation black-box testing framework based on image recognition

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.).

Text Classification Algorithms: A Survey

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

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

A curated list of Best Artificial Intelligence Resources

Coloring black and white images with deep learning.

A curated list of gradient boosting research papers with implementations.

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

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

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Machine Learning inference engine for Microcontrollers and Embedded devices