https://github.com/hackoregon/hack-university-machine-learning
Hack University course "Introduction to Machine Learning" sylabus, course material, python examples, resource links, and data sets
https://github.com/hackoregon/hack-university-machine-learning
Last synced: about 1 year ago
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Hack University course "Introduction to Machine Learning" sylabus, course material, python examples, resource links, and data sets
- Host: GitHub
- URL: https://github.com/hackoregon/hack-university-machine-learning
- Owner: hackoregon
- Created: 2016-01-30T23:44:09.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2016-09-28T20:03:34.000Z (over 9 years ago)
- Last Synced: 2025-02-02T04:23:31.464Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 47.9 MB
- Stars: 18
- Watchers: 13
- Forks: 14
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGES.rst
- License: LICENSE.txt
- Authors: AUTHORS.rst
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README
# Hack University: Machine Learning
Everything you need for the winter semester of [Hack Oregon](http://www.hackoregon.org/)'s
[Hack University](http://www.hackoregon.org/hack-university/) course
["Machine Learning"](http://www.hackoregon.org/database-cohort).
## Getting Started
### Install the Box
The best way to set up an environment for Machine Learning (and Data Science and Database Engineering) is to [install the Hack University virtual box](docs/install.md). If you're the adventurous type, or you already do all your work on a Linux box, then you can just install the requirements mentioned in the [syllabus](docs/syllabus.md) for each section of the course.
## [Syllabus](docs/syllabus.md)
## [Slides](docs/slides/README.md#slides)
## Videos
## Code
## [External Resoures](docs/resources.md)
### [Books](docs/books.md)
### [Contributors](docs/contributors.md)
- [Hobson](http://hobsonlane.com/)
- [Zeke](http://ze6ke.com/)
- [Hannes](http://hanneshapke.github.io/)
- [Cole](http://uglyboxer.github.io/)
- [Thunder](http://thundershiviah.github.io/)
- [Ebrahim](https://www.linkedin.com/in/safadi/)