Get Started with ML

Women Techmakers Lightning Talk at GDG Seattle meetup.
Tips and tricks, and learning resources on how to get started with AI/ML.

Transcript

1. Get Started with AI/ML WTM Lightning Talks @GDG Seattle Margaret Maynard-Reid, 9/25/2017 @margaretmz
2. @margaretmz | #AndroidDev | #MachineLearning Tips and Tricks • Start out easy and simple - ◦ ML Recipes by Josh Gordon ◦ Cloud AI Adventures by Yufeng Guo ◦ Siraj Raval’s videos on YouTube ◦ Make apps by REST APIs to ML services (such as the Vision API) ◦ Code labs, some of the TensorFlow code labs don’t require in-depth ML knowledge • Study prerequisites - ◦ linear algebra ◦ Python ◦ statistics • Understand the concepts under the hood 2
3. @margaretmz | #AndroidDev | #MachineLearning Learning Resources Online courses • Udacity - Intro to ML, Deep Learning Foundations ND, ML Engineer ND, AI ND • Coursera ◦ Machine Learning by Andew Ng ◦ Deep Learning Specialization by Andrew Ng ◦ Machine Learning Specialization by UW ← take the first course forcour an intro to ML • Stanford - CS231N on Convolutional Neural Networks for Visual Recognition • Kadenze - Creative Application of Deep Learning with TensorFlow 3
4. @margaretmz | #AndroidDev | #MachineLearning Learning Resources Books • Hands on machine learning with ScikitLearn and TensorFlow, by Aurélien Géron • Neural Networks and Deep Learning, a free online book • Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville 4
5. @margaretmz | #AndroidDev | #MachineLearning Learning resources Blog posts: • Machine Learning is Fun 6 posts by Adam Geitgey • I am trask by Andrew Trask, PhD student at University of Oxford • Colah’s blog by Christopher Olah, a ML researcher. • Pete Warden’s blog by Pete Warden, tech lead of TensorFlow mobile team at Google. • My blog post on how to Get Started with ML 5