这是基于Deepmat（ ）的CDL改编而成的用于链接预测（MAP）的关系深度学习（RDL）。 请转到example / README，以获取有关运行代码的更多说明。 要安装代码，请参阅类似的CDL流程。 参考： @inproceedings{DBLP:conf/aaai/WSY17, author = {Hao Wang and Xingjian Shi and Dit{-}Yan Yeung}, title = {Relational Deep Learning: {A} Deep Latent Variable Model for Link Prediction}, booktitle = {AAAI}, pages = {2688--2694},

调谐斯克莱恩 Tune-sklearn是Scikit-Learn的模型选择模块（GridSearchCV，RandomizedSearchCV）的替代品，它具有尖端的超参数调整技术。 产品特点 以下是tune-sklearn提供的功能： 与Scikit-Learn API的一致性：在标准Scikit-Learn脚本中更改少于5行即可使用API​​ []。 现代调整技术：tune-sklearn使您可以通过简单地切换几个参数来轻松利用贝叶斯优化，HyperBand，BOHB和其他优化技术。 框架支持：tune-sklearn主要用于调整Scikit-Learn模型，但它也支持并提供了许多其他带有Scikit-Learn包装器的框架的示例，例如Skorch（Pytorch）[ ]，KerasClassifier（Keras）[ ]，和XGBoostClassifier（XGBoost）[]。 向上扩展：Tune-sklearn利用 （一个用于分布式超参数调整的库）在不更改代码的情况下并行化多个核甚至多个机器上的交叉验证。 查看我们的和（针对master分支）。 安装 依存关

第二版 带详细目录 Bayesian Computation with R 使用R软件进行贝叶斯分析

Bayesian Data Analysis, Third Edition Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin CRC Press

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

Bayesian Analysis with Python Bayesian Analysis with Python

Solutions to some exercises from Bayesian Data Analysis, third edition, by Gelman, Carlin, Stern, and Rubin 22 Aug 2014

关于贝叶斯统计方面的很好的入门教材。The purpose of the book is to familiarize the students with the basic concepts of Bayesian theory and to quickly get them performing their own data analyses using Bayesian com- putational tools.

Mechine Learning A Bayesian and optimization perspective