MachineLearning

This page is for people who are interested in machine learning. If you are interested in learning more, feel free to stop by Noisebridge on Wednesdays from 6:30 - 7:30 p.m. for a our weekly class on machine learning. Each week we discuss a new topic as well as a selection of implementation notes that can help you apply machine learning to your projects of choice.

This class is continually evolving as we get user feedback. For updates regarding the progress to date, this weeks topics and readings, as well as a selection of machine learning resources, please visit:

https://github.com/AlephTaw/Hackers_Introduction_to_Machine_Learning

If you are interested in jumping in and are new to python, the scikit-learn ecosystem, or if you would like to review some of the mathematical foundations of machine learning, here are some materials which you may find help you get the most out of the class discussions and activities:

Python 3:

https://docs.python.org/3/tutorial/

Pandas:

https://www.youtube.com/watch?v=5JnMutdy6Fw

Scitkit-Learn:

https://www.youtube.com/watch?v=L7R4HUQ-eQ0

Mathematical Foundations:

Linear Algebra:

https://www.khanacademy.org/math/linear-algebra/eola-topic

Calculus:

https://www.youtube.com/watch?v=wOHrNt9ScYs&list=PL590CCC2BC5AF3BC1&index=34

Probability:

https://www.khanacademy.org/math/probability

If you have questions about the course which cannot be answered here, feel free to stop by noisebridge or make an inquiry at: noisebridge.ml@gmail.com.