MachineLearning

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Link titleThis 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 weekly talk on machine learning.

Each week someone from the group discusses a new topic along with a selection of implementation notes that can help you apply machine learning to your projects of choice.

For a selection of references, resources, and materials feel free to visit:

https://github.com/AlephTaw/Hackers_Introduction_to_Machine_Learning

Talk Schedule:

(Machine learning talks will be on hiatus for the month of November 2016.)

October 26, 2016 (Wednesday: 7:00 pm): Ross Story - Convolution Neural Networks and Deep Learning

November 2, 2016 (Wednesday: 7:00 pm): (Open Slot)

November 9, 2016 (Wednesday: 7:00 pm): (Open Slot)

November 16, 2016 (Wednesday: 7:00 pm): (Open Slot)

November 23, 2016 (Wednesday: 7:00 pm): (Open Slot)

November 30, 2016 (Wednesday: 7:00 pm): (Open Slot)



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.

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