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lihang_algorithms

用python和sklearn两种方法实现李航《统计学习方法》中的算法

machine-learning-with-python

Python code for common Machine Learning Algorithms

machine_learning_model

机器学习基本模型算法介绍(附加案例)

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

mfif

Multi-focus image fusion: papers, datasets and results

milvus

An open source vector similarity search engine

multiverso

Parameter server framework for distributed machine learning

onlinelearning_basicalgorithm

Online Learning code: TG -> FOBOS -> RDA ->FTRL ->FTPRL -> FTML

paddle

PArallel Distributed Deep LEarning

pai

Resource scheduling and cluster management for AI

pegasos

Comparison of pegasos and smo

pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

pydti

seetafaceengine

simple_flow

simple realtime flow computation

spark-ffm

FFM (Field-Awared Factorization Machine) on Spark

spark-fm

A parallel implementation of factorization machines based on Spark

spark-fm-parallelsgd

Implementation of Factorization Machines on Spark using parallel stochastic gradient descent (python and scala)

spark-gbtlr

Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark

spark-knn

k-Nearest Neighbors algorithm on Spark

spark-libfm

An implement of Factorization Machines (LibFM)

statistical-learning-method_code

手写实现李航《统计学习方法》书中全部算法

swiftsnails

a parameter server for distributed machine learning applications

tensorflow

An Open Source Machine Learning Framework for Everyone

tensorflow2_tutorials_chinese

tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials

transmogrifai

TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning

tutorials

The "REST With Spring" Classes:

xflow

Distributed LR、 FM model on Parameter Server. FTRL and SGD Optimization Algorithm.

xgboost_realtime_predict_test

xgboost在线预测

ytk-learn

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).