Liangliangzhuang's repositories
R-tutorial
庄闪闪的可视化笔记
Research_writing_tips
科研写作技巧笔记
R_for_deep_learning_seminar
2022年8月13日统计之读云讲堂
Degradation-process-in-reliability
汇总退化过程在可靠性中应用代码。
rmarkdown-guide
R Markdown 指南（一本八字还没一撇的中文书）
MachineLearningNote
机器学习白板系列
d2l-zh-pytorch-slides
Pytorch版代码幻灯片
paper-reading
深度学习经典、新论文逐段精读
Reliability_dataset
Find/store datasets in the field of reliability
10-simple-rules-for-teaching-R-for-Data-Science
10 simple rules for teaching R for Data Science (talk for 2022 Cascadia R conference)
ailearning
AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
cosx.org
统计之都主站
deep-learning-with-r-notebooks
R notebooks for the code samples of the book "Deep Learning with R"
hugo-blog-en
My English blog built with Hugo
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.
multi-dagradation
多元退化过程汇总
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.
PredictiveMaintenance
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
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.
rethinking
Statistical Rethinking course and book package
Scientific-research
科研分享会
ShixiangWang
Shixiang Wang' GitHub Profile