- JavaScript for R
- JavaScript Date Reference
- GitHub - wchextrafont Tools for using fonts in R graphics
- GitHub - kcf-jacksonjsReact R package Modelling in R. Interactivity in JS. Best of both worlds.
- GitHub - andrewsalishinycssloaders Add CSS loader animations to Shiny outputs
- tidylogREADME.md at master · elbersbtidylog · GitHub
- Tune XGBoost with tidymodels and #TidyTuesday beach volleyball Julia Silge
- Announcing tidybayes and ggdist 2.1 - Matthew Kay - Blog
- Why I use R • Gordon Shotwell
- Wilcoxon test in R how to compare 2 groups under the non-normality assumption R-bloggers
- We're hitting R a million times a day - rstudioconf2020.pdf
- Push straight to prod API development with R and Tensorflow at TMobile - Heather & Jacqueline Nolis
- Bay Area Motorcycle Training Reservation System v49.00
- A Recipe for Training Neural Networks
- Project-oriented workflow - Tidyverse
- A Common API to Modeling and Analysis Functions • parsnip
- The tidymodels Package - Tidyverse
- glmnet webinar May 3, 2013 - YouTube
- How and when ridge regression with glmnet
- There is Always Prior Information Elements of Evolutionary Anthropology
- TensorFlow for R Neural style transfer with eager execution and Keras
- TensorFlow for R Attention-based Image Captioning with Keras
- TensorFlow for R Image-to-image translation with pix2pix
- TensorFlow for R Collaborative filtering with embeddings
- TensorFlow for R Winner takes all A look at activations and cost functions
- TensorFlow for R You sure A Bayesian approach to obtaining uncertainty estimates from neural networks
- Shiny - Modularizing Shiny app code
- snipprutilities.R at master · dgrtwosnippr · GitHub
- Peeling back the curtain – The Economist
- Fundamentals of Data Visualization
- Inference for Numerical Data DataCamp
- Using deep learning to generate offensive license plates
- Modeling in the Tidyverse – RStudio
- balance_classes — H2O 3.18.0.9 documentation
- Ten Rules for Negotiating a Job Offer - haseeb qureshi
- The Statistical Bootstrap and Other Resampling Methods - Burns Statistics
- HR Analytics Using Machine Learning to Predict Employee Turnover
- Time Series Deep Learning Forecasting Sunspots With Keras Stateful LSTM In R
- Semantic-UI-Forest, collection of design, themes and templates for Semantic-UI.
- Time Aware Tibbles • tibbletime
- Tidy Tools for Forecasting • sweep
- Tidy Anomaly Detection • anomalize
- python installing tensorflow on windows with gpu
- rsample • General Resampling Infrastructure
- Recipes - Pre Processing Tools
- blogdown Creating Websites with R Markdown
- Reticulated Shiny R-bloggers
- Command reference — Conda documentation
- Artificial Neural Networks & It's Applications - XenonStack Blog
- tfruns Track and Visualize Training Runs
- Tidy Characterizations of Model Performance • yardstick
- Preprocessing Tools to Create Design Matrices • recipes
- Introduction to cowsay
- Understanding PCA using Shiny and Stack Overflow data – RStudio
- Healthcare, Spark, H2O, EMR, Production - Adam Sullivan, Change Healthcare - YouTube
- Pomodoro at DuckDuckGo
- GitHub - jbubghostwriter A port of ghostwriter theme to Hugo.
- autoplotly - One Line of R Code to Build Interactive Visualizations for Popular Statistical Results - Yuan's Blog
- GitHub - swarm-labRvision Basic computer vision library for R
- Tidy Statistical Inference • infer
- tidypredict - tidypredict
- Spark Standalone Deployment in AWS
- usethis 1.0.0 (and 1.1.0) - Tidyverse
- Intro to AutoML + Hands-on Lab - Erin LeDell, Machine Learning Scientist, H2O.ai - YouTube
- The caret Package
- Using Shiny with Scheduled and Streaming Data · R Views
- Trustworthy Analysis of Online AB Tests Pitfalls,challenges and solutions
- Controlled experiments on the web survey and practical guide SpringerLink
- Applying the Delta Method in Metric Analytics A Practical Guide with Novel Ideas - 1803.06336.pdf
- [1304.7406] Uncertainty in Online Experiments with Dependent Data An Evaluation of Bootstrap Methods
- Why We (Usually) Don't Have to Worry About Multiple Comparisons - multiple2f.pdf
- Choice of the Randomization Unit in Online Controlled Experiment
- How Booking.com increases the power of online experiments with CUPED by Simon Jackson Booking.com Data Science
- Improving the Sensitivity of Online ControlledExperiments Case Studies at Netflix
- Online Experimentation at Microsoft
- GitHub - r-libcoro Coroutines for R
- Data, Code and Visualization The tale of two charts combined
- Deploying R Models with MLflow and Docker - mdneuzerling
- a ggplot2 grammar guide
- (JUST RELEASED) timetk 2.0.0 Visualize Time Series Data in 1-Line of Code R-bloggers
- Chapter 11. Deploying a model into production - Build a Career in Data Science
- Easily Create Presentation-Ready Display Tables • gt
- Call R from R • callr
- How we built a Shiny App for 700 users R-bloggers
- Coding the forward propagation algorithm Python
- Alternative Design for Shiny · R Views
- Creating APIs in R with Plumber
- Welcome Causal Inference
- Generalized Additive Models in R · A Free Interactive Course
- Incrementality Bidding & Attribution - YouTube
- When should I apply data normalizationstandardization
- Least squares as springs
- Create Tidy Data Frames of Marginal Effects for ggplot from Model Outputs • ggeffects
- Learning Statistics with R
- Adventures in R
- Bootstrap Statistics with Tidymodels to Compare Bicycle Helmets Daniel Hadley
- Feature Engineering and Selection A Practical Approach for Predictive Models
- Bayesian Analysis to Compare Models using Resampling Statistics • tidyposterior
- ROC curves and Area Under the Curve explained (video)
- infer • Tidy Statistical Inference
- Hyperparameter Tuning
- Bootstrap Methods and their Application (Cambridge Series in Statistical and Probabilistic Mathematics) A. C. Davison, D. V.