kellylinyingxin's repositories
AI_Clinician
Reinforcement learning for medical decisions
codeparkshare
Python初学者（零基础学习Python、Python入门）书籍、视频、资料、社区推荐
d2l-zh
《动手学深度学习》，英文版即伯克利深度学习（STAT 157，2019春）教材。面向中文读者、能运行、可讨论。
Deep-Learning-in-R
Workshop (6 hours): Deep learning in R using Keras. Building & training deep nets, image classification, transfer learning, text analysis, visualization
Deep-Learning-with-PyTorch-Tutorials
深度学习与PyTorch入门实战视频教程 配套源代码和PPT
disease_prediction
Maximum Likelihoodlums group project to predict disease using MIMIC4 data
eicu-code
Code and website related to the eICU Collaborative Research Database
HyperDL-Tutorial
深度学习教程整理 | 干货
Machine-Learning-in-R
Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
matplotlib-tutorial
Matplotlib tutorial for beginner
mimic-iv
Code and discussion around the MIMIC-IV database
mimic-omop
Mapping the MIMIC-III database to the OMOP schema
mimic3-benchmarks
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.
mimiciii-antibiotics-modeling
my work with Dr. Yuan Luo focuses on modeling antibiotic time courses for patients admitted to the ICU based on a variety of clinical parameters using data from the MIMICiii ICU database
mimiciii-tutorials
Tutorials in R, Rmd, and the MIMIC-III dataset for the University of Michigan SOCR and MDP programs.
mit-deep-learning
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
nCoV2019
Location for summaries and analysis of data related to n-CoV 2019, first reported in Wuhan, China
nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
owid-datasets
OWID Dataset Collection
pandas-tutorial
适合初级到中级晋升者，有了体系之后就看熟练度了。
pandas_exercises
Practice your pandas skills!
pycon-pandas-tutorial
PyCon 2015 Pandas tutorial materials
Python_Tutorials
Python tutorials in both Jupyter Notebook and youtube format.
ResearchDesign
Seminar Resesearch Class at UTD for PhD students in Criminology
sepsis3-mimic
Evaluation of the Sepsis-3 guidelines in MIMIC-III
tutorials
机器学习相关教程
Unsupervised-Learning-in-R
Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).