Craig A's repositories
dsreading
Readings in Data Science: theory and practice
shap
A unified approach to explain the output of any machine learning model.
iml
iml: interpretable machine learning R package
mid_sm
Squirrel Monkey MID Analysis
lares
Personal Library for Analytics and Machine Learning
midbox
MID analysis code
islrlabs
R programming labs for the book Introduction to Statistical Learning
ML-From-Scratch
Machine Learning From Scratch. Bare bones Python implementations of Machine Learning models and algorithms with a focus on transparency and accessibility. Aims to cover everything from Data Mining to Deep Learning.
imlplots
Create Interpretable Machine Learning plots and analyse them in a interactive Shiny dashboard
ggthemr
Themes for ggplot2.
pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
gramm
Gramm is a complete data visualization toolbox for Matlab. It provides an easy to use and high-level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
selbosh.github.io
Personal web site, "Tea & Stats", built with blogdown and Hugo
Neural-Networks-Demystified
Supporting code for short YouTube series Neural Networks Demystified.
blog
Data, code, and scripts for the analysis in the Mode blog.
pytudes
Python programs to practice or demonstrate skills.
Kaggle
Projects on Kaggle datasets
EffectiveTensorflow
TensorFlow tutorials and best practices.
sand
Statistical Analysis of Network Data with R
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
DemoNeuralNet
Toy project to create a simple working neural net in R
keras-resources
Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library
MLPB
Machine Learning Problem Bible | Problem Set Here >>
imbalanced-learn
Python module to perform under sampling and over sampling with various techniques.
mner
Constructing and optimizing low-rank second-order maximum noise entropy (MNE) models
nn-from-scratch
Implementing a Neural Network from Scratch
CorBinian
CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations