jamesjin63's repositories
AML_Analysis
Hierarchical Dirichlet Process for clustering 2500 Patients based on their molecular profile (genes + cytos). Machine Learning for Survival Analysis (DeepSurv , RSF , SVM Regressor, Cox Models , ...) and integration of HDP components into modelling for prognosis. Comparison of state of the art models and evaluation of molecular contributors for cumulative incidence , relapse free survival , survival after first CR and overall survival
Carbon-Monoxide-Poisoning-Case
just a test for push
China_full_map
Access the Full map of China, with Jiuduan Line of South China Sea（九段线）
chinaMapJsonData
about china map json data，各个省市县的json数据都在里面，最外面的datas.json是全国的
click_that_hood
A game where users must identify a city's neighborhoods as fast as possible
Clinic_Data_Description
Data explorations within clinical research
data-science-learning-resources
A collection of machine learning resources that I've found helpful (I only post what I've read!)
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
demo-bookdown
Test for Gitbook
ebird-best-practices
Working through using auk, EBD, and habitat covariates based on ebook from https://cornelllabofornithology.github.io/ebird-best-practices/
ESEUR-code-data
Code and data used to create the examples in "Evidence-based Software Engineering based on the publicly available data"
h2o-3
Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
h2o-tutorials
Tutorials and training material for the H2O Machine Learning Platform
Interpretable-machine-learning-in-CKD
This paper presents a machine learning study for predicting chronic kidney disease (CKD) progression risk using clinical data
Liver_fluke
This study aimed to elucidate the liver fluke in Southeast Asia by Machine learning techniques
machine-learning-in-PEP
machine learning algorithms were used to find the optimal prediction model through internal and external verification, and the specific relationship between the clinical characteristics of patients with CBDs and PEP was explored, so as to finally predict the risk of PEP
mlr3
mlr3: Machine Learning in R - next generation
myocarditis_cardiomyopathy_children
GBD myocarditis and cardiomyopathy in children
Paper-list-XNZ
The paper published by Professor Xiao-Nong Zhou
PDSwR2
Code, Data, and Examples for Practical Data Science with R 2nd edition (Nina Zumel and John Mount)
RBookdown
R for beginners
recipes
A preprocessing engine to generate design matrices
statsintro_python
Python modules and IPython Notebooks, for the book "Introduction to Statistics With Python"
Stock-scrape
Stock data scrape and visulizations
Stock-Visualize
The R and Python for stock data visualization
supervised-ML-case-studies-course
Supervised machine learning case studies in R! 💫 A free interactive course
Tidymodel
The code of machine learning with R
UkBio-Bank-BC
The BC data in ukb with EDA