Pinned Repositories
Degradation-process-in-reliability
汇总退化过程在可靠性中应用代码。
liangliangzhuang
MachineLearningNote
机器学习白板系列
R-tutorial
庄闪闪的可视化笔记
R_example
公众号[庄闪闪的成长手册]对应的R资料（代码+数据）
R_for_deep_learning_seminar
2022年8月13日统计之读云讲堂
Research_writing_tips
科研写作技巧笔记
rmarkdown-guide
R Markdown 指南（一本八字还没一撇的中文书）
sdp
Stochastic degradation process
Statistic-learning
统计专业研究生课程学习
liangliangzhuang's Repositories
liangliangzhuang/R_example
公众号[庄闪闪的成长手册]对应的R资料（代码+数据）
liangliangzhuang/R-tutorial
庄闪闪的可视化笔记
liangliangzhuang/liangliangzhuang
liangliangzhuang/Research_writing_tips
科研写作技巧笔记
liangliangzhuang/Degradation-process-in-reliability
汇总退化过程在可靠性中应用代码。
liangliangzhuang/R_for_deep_learning_seminar
2022年8月13日统计之读云讲堂
liangliangzhuang/rmarkdown-guide
R Markdown 指南（一本八字还没一撇的中文书）
liangliangzhuang/sdp
Stochastic degradation process
liangliangzhuang/MachineLearningNote
机器学习白板系列
liangliangzhuang/d2l-zh-pytorch-slides
Pytorch版代码幻灯片
liangliangzhuang/ElegantBookdown
liangliangzhuang/paper-reading
深度学习经典、新论文逐段精读
liangliangzhuang/Reliability_dataset
Find/store datasets in the field of reliability
liangliangzhuang/10-simple-rules-for-teaching-R-for-Data-Science
10 simple rules for teaching R for Data Science (talk for 2022 Cascadia R conference)
liangliangzhuang/academic-kickstart
liangliangzhuang/ailearning
AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
liangliangzhuang/cosx.org
统计之都主站
liangliangzhuang/deep-learning-with-r-notebooks
R notebooks for the code samples of the book "Deep Learning with R"
liangliangzhuang/hugo-blog-en
My English blog built with Hugo
liangliangzhuang/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
liangliangzhuang/multi-dagradation
多元退化过程汇总
liangliangzhuang/PdM
liangliangzhuang/Predictive-Maintenance-of-Aircraft-Engine
In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.
liangliangzhuang/PredictiveMaintenance
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
liangliangzhuang/PyTorch-Transformer-for-RUL-Prediction
Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit. Journal of Intelligent Manufacturing, 1-10.
liangliangzhuang/rethinking
Statistical Rethinking course and book package
liangliangzhuang/rmarkdown-xaringan-slides
liangliangzhuang/Scientific-research
科研分享会
liangliangzhuang/ShixiangWang
Shixiang Wang' GitHub Profile
liangliangzhuang/zll-package