liangliangzhuang Goto Github PK

10-simple-rules-for-teaching-r-for-data-science

10 simple rules for teaching R for Data Science (talk for 2022 Cascadia R conference)

2019-ncov-japan

🦠 Interactive dashboard for real-time recording of COVID-19 outbreak in Japan

academic-kickstart

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

d2l-zh-pytorch-slides

Pytorch版代码幻灯片

deep-learning-with-r-notebooks

R notebooks for the code samples of the book "Deep Learning with R"

deep_uncertainty_estimation

This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as described in "A General Framework for Uncertainty Estimation in Deep Learning" (Loquercio, Segù, Scaramuzza. RA-L 2020).

degradation-process-in-reliability

汇总退化过程在可靠性中应用代码。

dl-keras-tf

rstudio::conf(2020) deep learning workshop

elegantbookdown

elegantpaper

Elegant LaTeX Template for Working Papers

hugo-blog-en

My English blog built with Hugo

hugo-theme-stack

Card-style Hugo theme designed for bloggers

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

machinelearningnote

机器学习白板系列

multi-dagradation

多元退化过程汇总

multi-rig

paper-reading

深度学习经典、新论文逐段精读

pdm

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

python

Python脚本。模拟登录知乎， 爬虫，操作excel，微信公众号，远程开机

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.

r-tutorial

庄闪闪的可视化笔记

r4ds-exercise-solutions

Exercise solutions to "R for Data Science"

reliability_dataset

Find/store datasets in the field of reliability

research_writing_tips

科研写作技巧笔记

rethinking

Statistical Rethinking course and book package