johnmyleswhite/ML_for_Hackers
johnmyleswhite/ML_for_Hackers has 3,732 GitHub stars and 2,171 forks. GitHot measured +1 stars in 24 hours. Last checked 2026-11-06 18:18 UTC. Last push 2019-05-26.
Code accompanying the book "Machine Learning for Hackers"
Measured star growth
- in 24h
- +1
- in 7 days
- Update delayed
- in 15 days
- Update delayed
- in 1 month
- Update delayed
Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.
README.md
OriginalCode for Machine Learning for Hackers
This repository contains all of the code examples for Machine Learning for Hackers (2012). The code may not appear exactly as it does in the text, as additional comments and modifications may have been added since publication.
Getting started
The code in this book relies on several R libraries. Two libraries, RCurl and XML require additional software to be installed:
- http://curl.haxx.se/ (for
RCurl) - http://xmlsoft.org/ (for
XML)
To make sure you have all of the requite libraries run the package_installer.R script. In your R console type the following:
> source("package_installer.R")
When running the installer inside R you will be asked where to save the library files. If you'd like to install the libraries globally, you can run script at the command-line with admin privileges:
$ sudo RScript package_installer.R
Authors
- Drew Conway, Department of Politics, New York University http://drewconway.com/
- John Myles White, Data Science, Facebook http://www.johnmyleswhite.com/
License
All source code is copyright (c) 2012, under the Simplified BSD License.
For more information on FreeBSD see: http://www.opensource.org/licenses/bsd-license.php
All images and materials produced by this code are licensed under the Creative Commons Attribution-Share Alike 3.0 United States License: http://creativecommons.org/licenses/by-sa/3.0/us/
Explore related projects
tensorflow/tensorflow
An Open Source Machine Learning Framework for Everyone
201,367 starshuggingface/transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
168,609 starsAUTOMATIC1111/stable-diffusion-webui
Stable Diffusion web UI
165,245 starsComfy-Org/ComfyUI
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. The fastest local inference engine in the world.
145,470 stars