René's URL Explorer Experiment


Title: Pearson Lab at Duke University

direct link

Domain: pearsonlab.github.io

NoneIE=edge
theme-color#ffffff

Links:

[ λ ]https://pearsonlab.github.io/
Abouthttps://pearsonlab.github.io/about.html
Bloghttps://pearsonlab.github.io/blog/
Join Ushttps://pearsonlab.github.io/join_us.html
Learning (current)https://pearsonlab.github.io/learning.html
Find Ushttps://pearsonlab.github.io/location.html
Peoplehttps://pearsonlab.github.io/people.html
Publicationshttps://pearsonlab.github.io/publications.html
Researchhttps://pearsonlab.github.io/research.html
Wikihttps://github.com/pearsonlab/pearsonlab.github.io/wiki
Learning to programhttps://pearsonlab.github.io/learning.html#learning-to-program
General commentshttps://pearsonlab.github.io/learning.html#general-comments
Choosing your first languagehttps://pearsonlab.github.io/learning.html#choosing-your-first-language
Learning your first languagehttps://pearsonlab.github.io/learning.html#learning-your-first-language
In additionhttps://pearsonlab.github.io/learning.html#in-addition
Python for Data Sciencehttps://pearsonlab.github.io/learning.html#python-for-data-science
Statisticshttps://pearsonlab.github.io/learning.html#statistics
Machine Learning: Classichttps://pearsonlab.github.io/learning.html#machine-learning-classic
Machine Learning: Deep Learninghttps://pearsonlab.github.io/learning.html#machine-learning-deep-learning
Noteshttps://pearsonlab.github.io/learning.html#notes
StackOverflowhttps://stackoverflow.com/
there are a lot of guidelines for posting a good questionhttps://stackoverflow.com/help/how-to-ask
1https://pearsonlab.github.io/learning.html#fn:sof_os
belowhttps://pearsonlab.github.io/learning.html#python-for-data-science
elsewherehttps://pearsonlab.github.io/blog/2016/07/13/investing-in-julia.html
RStudiohttps://www.rstudio.com/
everythinghttps://www.tidyverse.org/
byhttp://r4ds.had.co.nz/
Hadley Wickhamhttp://adv-r.had.co.nz/
2https://pearsonlab.github.io/learning.html#fn:matlab_woes
Whirlwind Tour of Pythonhttps://jakevdp.github.io/WhirlwindTourOfPython/
scientific programminghttps://pearsonlab.github.io/learning.html#python-for-data-science
Fluent Pythonhttp://shop.oreilly.com/product/0636920032519.do
Python Data Science Handbookhttps://jakevdp.github.io/PythonDataScienceHandbook/
Data Analysis Using Regression and Multilevel/Hierarchical Modelshttp://www.stat.columbia.edu/~gelman/arm/
Stanhttp://mc-stan.org/
A First Course in Bayesian Statistical Methodshttps://www.stat.washington.edu/people/pdhoff/book.php
All of Statisticshttps://www.amazon.com/All-Statistics-Statistical-Inference-Springer/dp/0387402721/ref=sr_1_1?ie=UTF8&qid=1249141007&sr=8-1
STA 663https://github.com/cliburn/sta-663-2021
An Introduction to Statistical Learninghttps://www.statlearning.com
Elements of Statistical Learninghttp://web.stanford.edu/~hastie/ElemStatLearn/
Pattern Recognition and Machine Learninghttps://www.springer.com/us/book/9780387310732
pdfhttp://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf
Machine Learning: A Probabilistic Perspectivehttps://probml.github.io/pml-book/
Deep Learning Bookhttp://www.deeplearningbook.org/
Stanford convnets classhttp://cs231n.stanford.edu/
Deep Learning Specializationhttps://www.coursera.org/specializations/deep-learning
3https://pearsonlab.github.io/learning.html#fn:online_dl_classes
TensorFlowhttps://www.tensorflow.org/
PyTorchhttps://pytorch.org/
JAXhttps://github.com/google/jax
↩https://pearsonlab.github.io/learning.html#fnref:sof_os
↩https://pearsonlab.github.io/learning.html#fnref:matlab_woes
↩https://pearsonlab.github.io/learning.html#fnref:online_dl_classes

Viewport: width=device-width, initial-scale=1

URLs of crawlers that visited me.