DanburyAI/SG_DLB_2017

Repo for our deep learning book study group launched in October 2017.

Danbury Artificial Intelligence

Deep Learning Study Group

A repo for our deep learning book study group launched in October 2017. This is a living repo that is subject to rapid change. Also, most work is in progress, and nothing should be taken as final unless marked so. If you'd like to contribute, join our meetup group and message the organizers.

Featured Jupyter Notebooks

In this group we aim to disseminate knowledge through code, prose, and mathematics -- a lovely combination that Jupyter Notebooks provide. Here are our best Notebooks so far.

Linear Algebra

• Linear Vs. Non-Linear Functions - Andrew Ribeiro
• Matrix as a Function & Plotting Vectors - Andrew Ribeiro

Probability, Statistics, and Information Theory

• Ch 3.13, Information Theory - Lambert Wixson
• Expectation, Variance, and Covariance - Andrew Ribeiro

Numerical Computation

• Example - Gradient of Linear Least Squares - Michael Rogowski

Machine Learning Basics

• Linear Regression - The Solution Space
• Linear Regression - Gradient Descent

Most Active Members

• Andrew Ribeiro
• Michael Rogowski
• Lambert Wixson
• Doug Cowles

About Danbury AI

Danbury AI is a public AI meetup group hosted by the Danbury Hackerspace that aims to stimulate discussion in the vast field of artificial intelligence and bring together locals that foster a passion for the field. We hold our in person meetings on the first Tuesday of every month at which we host a variety of presenters, discussions, and workshops. We maintain a lively web presence via slack so the conversation never stops.