darthy's repositories
awesome-causality-algorithms
An index of algorithms for learning causality with data
burlap
Repository for the ongoing development of the Brown-UMBC Reinforcement Learning And Planning (BURLAP) java library
deeplearning4j
Deep Learning for Java, Scala & Clojure on Hadoop & Spark With GPUs - From Skymind
dl4j-examples
Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)
GCN_study
GCN 入门学习教程
GGMprojpred
Bayesian graphical models estimated with projection predictive selection
guava
Google Core Libraries for Java 6+
introduction2CausalInference
my practice for causal inference in R
introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
librec
LibRec: A Java Library for Recommender Systems, see
mahout
Mirror of Apache Mahout
meka
Multi-label classifiers and evaluation procedures using the Weka machine learning framework.
MLSTM-FCN
Multivariate LSTM Fully Convolutional Networks for Time Series Classification
moa
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
NLP-Interview-Notes
该仓库主要记录 NLP 算法工程师相关的面试题
Rcourse_on_github
my practice on GitHub and linear models in R
Recommend-System-tf2.0
原理解析及代码实战，推荐算法也可以很简单 🔥 想要系统的学习推荐算法的小伙伴，欢迎 Star 或者 Fork 到自己仓库进行学习🚀 有任何疑问欢迎提 Issues，也可加文末的联系方式向我询问！
Recurrent-Point-Process
Modeling the asynchronous event sequence via Recurrent Point Process
reinforcement-learning-an-introduction
Python code for Reinforcement Learning: An Introduction
RS_paper_study
推荐系统学习笔记
smile
Statistical Machine Intelligence & Learning Engine
StructED
Risk Minimization Algorithms in Structured Prediction
test
test for R
TimeGAN
Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019
toolbox
A Java Toolbox for Scalable Probabilistic Machine Learning
variableImportance
practice on variable importance measure (VIM) in the context of explainable ML or causal inference