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## Jason’s Machine Learning 101 – Google Slides

Best tutorial on ML I’ve seen yet. docs.google.com/presentation/d/1kSuQyW5DTnkVaZEjGYCkfOxvzCqGEFzWBy4e9Uedd9k/preview?imm_mid=0f9b7e&cmp=em-data-na-na-newsltr_20171213&slide=id.g2923c61c4e_0_33

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## Lie group

Lie groups for AI. Basically trying to understand how useful unitary matrices are for these problems. tacocohen.files.wordpress.com/2014/05/tsa_icml.pdf

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## Education – Google AI

Google AI education link ai.google/education/

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## Machine Learning for Humans, Part 4: Neural Networks & Deep Learning

Great tutorial on ML.

medium.com/machine-learning-for-humans/neural-networks-deep-learning-cdad8aeae49b

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## GitHub – mattnedrich/GradientDescentExample: Example demonstrating how gradient descent may be used to solve a linear regression problem

Some simple Python example code to play around with gradient decent. github.com/mattnedrich/GradientDescentExample

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## An Introduction to Gradient Descent and Linear Regression

Great into to gradient descent. Nice little examples for beginners. spin.atomicobject.com/2014/06/24/gradient-descent-linear-regression/

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## Introduction to Statistical Learning

Free book intro to statistical learning. www-bcf.usc.edu/~gareth/ISL/index.html

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## SiP for

SiP for neural networks www.ece.ust.hk/~eexu/OPTICS2018/Bert%20Offrein.pdf

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## Activation function – Wikipedia

Activation function for a neuron. en.wikipedia.org/wiki/Activation_function

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