snowdj Goto Github PK

dl-keras-tf

rstudio::conf(2020) deep learning workshop

dl-workshop

A deep learning workshop, done from scratch, taught using autograd.

dl_class_2017_may

七月算法深度学习五月班课件

dl_tutorials_4th

dlaicourse

Notebooks for learning deep learning

dlbook_exercises

Exercises for the Deep Learning textbook at www.deeplearningbook.org

dml

Double Machine Learning for approximately unbiased inference

docker_practice

Learn and understand Docker technologies, with real DevOps practice!

doing-bayesian-data-analysis

MY R code from the book (2nd Edition) by John K. Kruschke

doing-bayesian-data-analysis-in-brms-and-the-tidyverse

Working through Kruschke’s text one file at a time

doing-meta-analysis-in-r

All R codes for the guide "Doing Meta-Analysis in R"

doing_bayesian_data_analysis

Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke

doing_data_science

This is the example code repository for Doing Data Science by Cathy O'Neil and Rachel Schutt (O'Reilly Media)

donskerclass.github.io

douban.fm

:radio: douban.fm based on Python

doubleml-python

dowhy

DoWhy is a Python library that makes it easy to estimate causal effects. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

dp4ss-textbook

Data Programming for Social Scientists intro to R programming textbook.

dp_growth_kerk

dpdd-snippets

R scripts & snippets supporting Data Science & Analytics Branch (OCIO) workflows 👩‍💻👨‍💻

dplyr

Plyr specialised for data frames: faster & with remote datastores

dplyrtutorial

drake-intro

Reproducible Data Workflows with Drake

drop-out-prediction

drop-out-prediction-analysis

dropout-mooc-kddcup2015

Dropout rate prediction in MOOC, for KDDCUP 2015

dropoutrateresearch

ds-intro-to-r-2-day

Lessons for a 2-day Introduction to Data Science using R Workshop

ds4ps-quarto-example

ds4se

Data Science for Software Engineering