Stars
🥪🦘 An open source sandbox project exploring dbt workflows via a fictional sandwich shop's data.
A course on aligning smol models.
Course Files for Complete Python 3 Bootcamp Course on Udemy
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These vide…
This is a Cross-Platform Plot Manager for Chia Plotting that is simple, easy-to-use, and reliable.
Collected opinions and advice for academic programs focused on data science skills.
A next-generation curated knowledge sharing platform for data scientists and other technical professions.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
Turning geospatial polygons into regular or hexagonal grids. For other similar functionality see the tilemaps package https://github.com/kaerosen/tilemaps
Resources for text book "System Dynamics Modeling with R"
A template for bootstrapping reproducible RMarkdown documents for data journalistic purposes.
Big Data Pipeline workshop code of SG dataday 2017
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …
🔧 R package: startup - Friendly R Startup Configuration
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
An R Dataset Package for US Beer Statistics From TTB 🍺
Links to slides for talks at the 2016 Joint Statistical Meetings in Chicago
📊 Path to a free self-taught education in Data Science!
useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html
machine learning and deep learning tutorials, articles and other resources
An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.)
Instructions for setting up the software on your deep learning machine