Advanced Deep Learning with Keras, published by Packt

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Probabilistic reasoning and statistical analysis in TensorFlow

Code repository for Deep Learning with Keras published by Packt

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Github repository associated with Toronto Probabilistic Programming meetup

Public facing notes page

Deep Learning Tutorial notes and code. See the wiki for more info.

Tutorial files to accompany Sorensen, Hohenstein, and Vasishth paper: http://www.ling.uni-potsdam.de/~vasishth/statistics/BayesLMMs.html

Example models for Stan

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Implementing a Neural Network from Scratch

Talks, slides, notebooks, and code snippets

Unison file synchronizer

RStan, the R interface to Stan

scikit-learn: machine learning in Python

Interactive Web Plotting for Python

A curated list of awesome Python frameworks, libraries and software

A collection of useful .gitignore templates

Advanced R programming: a book

logstash - transport and process your logs, events, or other data

Statistical Rethinking course and book package

RImpala is an R package that helps you to connect and execute distributed queries using Cloudera Impala

Tutorial material on the scientific Python ecosystem

A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstartes basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning t…

PyMC: Bayesian Stochastic Modelling in Python