How to Organize an ML Study Jam - NA GDE Summit 2019

I get these questions a lot: "how do I organize an ML Study Jam"? "Where do I find the ML content"? So I gave this talk "How to Organize an ML Study Jam" at the North America GDE Summit 2019, Toronto Canada.

There are tons of great resources, for example, courses from tensorflow.org, Udacity, Coursera, MIT and Kaggle Learn.

Hopefully this helps you whether you are organizing an ML Study Jam for your meetup, a study group or study ML on your own.

Transcript

1. How to Organize an ML Study Jam Best practices & learning resources Margaret Maynard-Reid ML GDE @margaretmz North America GDE Summit 1
2. “AI is the new electricity” - Dr. Andrew Ng, 4/28/2017 2
3. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Why run an ML Study Jam? Because ML skills are in high demand ML is the “Software 2.0” (Andrej Karpathy), every engineer and non engineer should learn the basics of ML. 3
4. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Before • Remind attendees of prerequisites prior to the event • Identify content Study Jams best practices During • Talks • Hands-on • Coaches • Demos • Swags After • Social media & photos • Follow-up 4 Single day or multiple day sessions My blog post on How to Organize a Study Jam
5. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 ML prerequisites Python & Python libs • Python basics • Numpy - low level math operations • Matplotlib - data visualization • Pandas - data manipulation Calculus • Derivative • Gradient • Chain rule Algebra & linear algebra Stats 5
6. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Google Colab What is Google Colab? • Jupyter Notebook ◦ stored on Google Drive ◦ running on Google’s VM in the cloud • Free GPU and TPU! • TensorFlow is already installed • Save and share from your Drive • Save directly to GitHub Check out these learning resources • My blog on Colab • TF team’s blog on Colab • Laurence’ Video Build a deep neural network in 4 mins with TensorFlow in Colab • Paige’s video How to take advantage of GPUs & TPUs for your ML project • Sam’s blog Keras on TPUs in Colab 6
7. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Study Jam content Where to find the ML content? From challenging to easy, mix and match these strategies Use existing content Write your own Invite an expert 7
8. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Write your own content Pros: • Re-use your own code, tutorial and blog posts • Greatest flexibility Cons: • Time consuming 8
9. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Blog.tensorflow.org TensorFlow on Youtube TensorFlow on Twitter #AskTensorFlow #TensorFlowMeets TensorFlow Dev Summit 2019 9 Start with tensorflow.org
10. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 MOOCs Udacity, Coursera and MIT all have deep learning course with TensorFlow 2.0 2 month, intermediate 1 month, 4 courses 5 session. 9 lectures link link link 10
11. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Machine Learning Crash Course Developed by Google Pros: • Great ML fundamentals • Nice animated explanations, for example - ◦ Optimizing learning rate ◦ Backpropagation • Complete ML glossary Cons: • TensorFlow code in outdated version 11
12. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Qwiklabs 12 Go to qwiklabs.com and search for “ML”: • Baseline: Data, ML, AI • Advanced ML: ML Infrastructure • Intro to ML: Image Processing • Intro to ML: Language Processing • Intermediate ML: TensorFlow on GCP
13. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Kaggle Learn 13
14. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Idiomatic Programmer Andrew Ferlitsch https://github.com/GoogleCloudPlatform/keras-idiomatic-programmer 14
15. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 Recommended books By Aurélien Géron Deep learning with Python by Francois Chollet 15
16. @margaretmz | #ML | @GoogleDevExpert | #NAGDESummit2019 How to read research papers • Arxiv.org • arxiv-sanity.com • Papers with code 16
17. Thank you! Follow me on Twitter, Medium & GitHub to learn more about on-device ML, TensorFlow & computer vision. @margaretmz @margaretmz margaretmz Margaret Maynard-Reid ML GDE @margaretmz North America GDE Summit 17