A curated list of awesome algorithmic trading frameworks, libraries, software and resources

VIP cheatsheets for Stanford's CS 230 Deep Learning

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

VIP cheatsheets for Stanford's CS 229 Machine Learning

BYU course on visualizing data with R

Distributed Deep learning with Keras & Spark

DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.

moDel Agnostic Language for Exploration and eXplanation

R Interface to Keras

Reference implementations of popular deep learning models.

Use VGG19 to build an image style transfer in TensorFlow.

A minimal tutorial on how to build a neural network classifier based on the iris data set using Keras/TensorFlow in R/RStudio

R project in Google Summer of Code 2018

Automatic extraction of relevant features from time series:

An interactive free online short course on the drake R package

Distance Covariance Analysis

energy package for R

Tools for creating tuning parameter values

🛠️ 📊 Tools for Exploring and Comparing Data Frames

Apply Mapping Functions in Parallel using Futures

A cross-platform launcher that simply works

The most recent version of the Applied Machine Learning notes

A tidy unified interface to models

Easily install and load the tidymodels packages

Tidy Messy Data

Supplementary material for Hands-On Machine Learning with R, an applied book covering the fundamentals of machine learning with R.

An R package implementing Rubin's (1981) Bayesian bootstrap.

Probabilistic reasoning and statistical analysis in TensorFlow