Machine Learning Blogs and Resources

Title	Details	Website
My Machine Learning Cookbook - Jeffrey Long	Machine Learning in R with tidymodels, {parsnip}, {tidymodels}, {broom.mixed}, {rstan}, {skimr}, {yardstick}	jeffreyCarlLong GitHub R Vignette
{tidymodels}	Hadley Wickham brings ML to R tidy()	tidy package
{broom}	Tidies 100+ models from popular modeling packages and almost all of the model objects in the stats package that comes with base R, tidy(), glance(), augement(), vignette("broom")	broom package
{recipes}	Feature engineering steps to process data, step_date(), step_holiday(), step_rm(), convert indicator variables to one hot encoding	recipes package
{workflows}	pairs a model and a recipe together workflow(), add_model(), add_recipe()
{rsample}	Data splitting to create training and testing sets, initial_split(), training(), testing()	rsample package
{rstanarm}	Bayesian prior distributions for rstanarm models, stan_glm(), prior, prior_intercept, linear_reg	rstanarm package
{parsnip}	Train models with different engines, model type (random forests, linear regression, LSVM), mode (classification, regression), computational engine (R packages, methods), set_engine()	parsnip package, parsnip models
{yardstick}	ROC curves, predicted model metrics, roc_curve() and roc_auc()	yardstick package
easystats: Quickly investigate model performance	Inspiration to learn tidymodels	R Bloggers
Mixing centered and non-centered parameterizations in a hierarchical model with PyMC3	Hierarchical models	Joshua Cook
Meetup slides: Introducing Deep Learning with Keras	General Keras slides	Shirin's playgRound
How to call bullshit on AI companies (aka a short lesson on recall)	precision, recall, accuracy	Cartesian Faith
ML models: What they can’t learn?	True model plots	R Bloggers
Automated Feature Selection Using bounceR	GitHub Repo	Statworx
Machine Learning Yearning	Andrew Ng	Book Chapters 1-14
Machine Learning Crash Course	TensorFlow APIs	Google Course
Machine Learning Modeling in R	Cheat sheet	The R Trader
scikit-learn Clustering	sklearn metrics datasets numpy clustering	Documentation
TensorFlow for Poets	Python Notebook for ML	Gist
Google Calab	Train your ML Model 4 FREE	Upload Python Notebook
Train Your Machine Learning Models on Google’s GPUs for Free — Forever	Google Collab	Hackernoon
15 Types of Regression You Should Know	Stats, fit code, ggPlots	Listen Data
TensorFlow for R	Slides and Book recommendations	R-bloggers
Fitting a TensorFlow Linear Classifier with tfestimators	TensorBoard visualization tool, Titanic data set	R-bloggers
TensorFlow	Machine Learning API from Google	TensorFlow Basics
MNIST	Machine learning with TensorFlow	MNIST TensorFlow
What's the difference between data science, machine learning, and artificial intelligence?	Good explanation in lay language	David Robertson's Blog- Variance Explained
Building a neural network from scratch in R	Is it a hot dog?	Tea & Stats, data science with David Selby
Deep Learning from first principles in Python, R and Octave	Decision boundary with hidden units i and learning rate j	Giga Thoughts Part I, and Part II